e-Proceeding ICo-ASCNITech2022

2. LITERATURE REVIEW 2.1 COLOUR SENSOR AND IDENTIFICATION In automated applications, colour sensor systems are being gradually replaced in order to detect automation failures and monitor quality at the speed of the production line. They are used in production lines to distinguish products by colour. There have been identified eleven basic colour names: white, grey, black, red, yellow, green, blue, orange, purple, pink, and brown. The majority or all colours can be described by their variations and combinations. According to (Kunhimohammed et al, 2016), since human colour vision is facilitated in part by three distinct types of cone cells in the retina, three values are required and sufficient to define any colour. (Ch.Shravani et al, 2019) define colour in space with coordinates of hue, saturation, and intensity (HSI) in colour science. The hue of a colour is determined by the wavelength of white light reflected by it. Intensity (lightness) quantifies the degree of whiteness or grey scale of a particular colour. Saturation is a measurement of a colour's vibrancy. The term chromaticity encompasses primarily hue and saturation components. 2.2 DEFINITION OF LIGHT Light is an electromagnetic radiation within a specific portion of the electromagnetic spectrum; the term typically refers to visible light, which is perceptible by the human eye and responsible for the sense of sight. In physics, the term light is sometimes used to refer to electromagnetic radiation of any wavelength, visible or not. According to (Zwinkels & Joanne, 2015), light is also synonymous with electromagnetic radiation, which includes not only ultraviolet, visible, and infrared spectrums, but also X-ray, gamma-ray, and radio spectrums. 2.3 THE RELATIONSHIP BETWEEN COLOUR AND LIGHT Colour is a brain sensory experience, and only in the presence of light is it possible to perceive colour. Sir Isaac Newton found that white light is comprised of a spectrum of colours, specifically Red, Orange, Yellow, Green, Blue, and Violet. Only when light strikes an object is its characteristic colour revealed, and there are only three ways in which an object can interact with light rays. When all light rays are absorbed, the human eye perceives black; when all are reflected, it perceives white; and when all but one are absorbed, it perceives the reflected colour. For example, an apple is red. The apple appears red under white light because it reflects light in the red portion of the spectrum and absorbs light at other wavelengths. If red is removed from the light source using a filter, the apple will reflect very little light and appear black. Each colour has a distinct wavelength that is processed, recognised, and transmitted to the brain by the eye. The rods and cones of the eye's retina recognise the colours of light and the degree of black and white, allowing for the perception of the colour characteristics of objects. This information is then translated by the brain for perception by the human eye. Red, green, and blue are the three primary colours that represent RGB space; all other colours are derived from these three colours. The three relevant components of the RGB colour space. And it will be modified accordingly if the brightness is altered (Neal et al, 2018). Colour and texture are the defining characteristics of natural images and play a crucial role in visual perception. (Bresilla et al, 2019) concentrated on the colour of ripe fruit. Colour is frequently a distinctive and revealing indicator of the presence of fruit. The majority of ripe fruits have a distinct hue. For example, apples, strawberries, and peaches are typically red. The colour orange is a synonym for oranges. Yellow indicates that pears, lemons, peaches, and bananas are ripe. When they are ready to be picked, they stand out from the surrounding greenery. 3. METHODS By (M. Khojastehnazhand et al, 2010), many farmer associations give automated grading of agricultural products a high priority due to the constant need to produce high-quality food items in a timely manner. Colour sorting machines provide farmers and the food industry with significant relief by reducing their workload. These machines are equipped with a colour sensor that can detect the hue of any object. For this project, the colour sorting machine will colour-sort the fruits. It can be done quickly by sight, but when there are a large number of objects to sort, the process becomes tedious and automatic colour sorting machines are advantageous. In addition, a fruit detector will identify the type of fruit inserted into the machine. The top 88

servo ensures the fruit is delivered after the fruit name has been identified, which moves the fruit from the detector to the colour sensor, which detects the fruit's colour, and then to the dropping hole using a slider platform controlled by a bottom servo. After colour detection, a servo motor will grasp the fruit and place it in the appropriate box. The fruit is transported by a slidable platform to a group of containers where coloured fruits are stored. Arduino is an open source microcontroller which can be easily programmed, erased and reprogrammed at any instant of time (Leo louis, 2016). This project sorts fruits by colour using an Arduino board and a TCS3200 colour sensor. Texas Advanced Optoelectronic Solutions (TAOS) developed the programmable colour light-to-frequency converter Sensor Colour TCS3200. The programmable IC TCS3200 converts light into colour frequency with a box-shaped output signal (Trong et al, 2018). The photodiode currentto- frequency converter and sensor as the two major components of this colour. The TCS3200 colour sensor light is outfitted with a filter and an RGB light base. According to (Lim and Irda, 2014), a colour sensor recognizes the colour of an object by using the green, blue, and red filters to detect a common colour and then determining which colour filter has the highest recorded value. The light intensity of LEDs varies with the detectable surface darkness of fruits. The photodiode's filters capture only one colour and exclude the others (P. Rajkumae et al, 2021). Figure 1 show the Photodiode Spectral Responsivity as taken from data sheet TCS3200 colour sensor. Note that the results differ due to the various photodiode types sensitivity levels, as shown in the sensors datasheets photodiode spectrum responsivity diagram. As stated in diagram, the blue detector corresponds to about the lower one of the visible spectrums, the green detector corresponds to the middle, and the red detector corresponds to the upper one. Figure 1: Photodiode Spectral Responsivity. The physical structure for this project is made of PVC board that has been cut and glued. The Arduino Nano serves as the primary controller, to which the colour sensor and servo motors are connected. It then transmits a command to the servo motors after analysing the data from the colour sensor. Attached facing downward, the colour sensor examines the fruit's colour in accordance with a colour frequency and a custom function that aids in the identification of the fruit's colour. The fruit sample used for the testing is green grape for green colour, blueberry for blue colour and tomato cherry for red colour. 4. SYSTEM DEVELOPMENT The machine's body and storage compartment are constructed of a suitable plastic material. In this instance, PVC Board was used for the body, while PVC rigid sheet was used for the tube. After assembling both software and hardware, the machine is basically complete. The sensor's RGB (Red, Green, Blue) values will then be transmitted to the Arduino Nano for processing. It is necessary to create a programme for Arduino in order to correctly perform the colour sensing and recognition task. Before the design is confirmed and materials are purchased, the programming must be tested and a simulation conducted. There are numerous 89

ways to simulate, including using software on a computer and a breadboard. The breadboard simulation must be performed with basic components. After applying voltage and current to a circuit, it is essential to verify that the components and board are free of defects. If the programme is not functioning during the test or simulation, troubleshooting is crucial. Connecting all wires to the Arduino Nano, batteries, servo motor, and colour sensor completes the connection. During testing, the sorting system is observed and errors are checked for. Either one or both components must be modified if the combination of hardware and software contains errors or defects. The process of troubleshooting will be repeated until the project's objectives are met. As shown in Figure 2, the Colour Sorter's design and development are now complete. Figure 2: Colour Sorter 5. RESULT AND DISCUSSION The sorting mechanisms and tests are presented in the following sections in figure 3. In the discussion, the result is analysed and compared. The test carried out includes colour accuracy test. Figure 3: Experiment of the Project 5.1 Analysis For the first analysis, the test is carried out to determine the best colour of the fruits can detect by the colour sensor TCS3200. Table 1 shows the frequency limit of colour for the bottom and upper frequency for red, green and blue colours. There is a variety of types and colours of the fruits used for the first analysis, such as red colour, blue colour and green colour. 90

Table 1: Frequency limits of colour Colour Bottom frequency limits Upper frequency limits Red 25 120 Green 30 90 Blue 25 70 The result of the study is shown in Figure 4. To distinguish between different colours we have three conditions. When the R is the maximum value (in RGB parameters) we know we have a red object. When G is the maximum value, we know we have a green object. While when B is the maximum value, we know we have a blue object. Based on the result analysis, slight inaccuracy shows between the colour of the fruits is due to an error of detection. The regular error happened due to the improper position of the fruit. Because these colours are so similar, the colour is not well detected when the fruits are not well positioned under the colour sensor. This issue could be resolved by using a different parameter, luminance, to distinguish between the fruits or by improving the positioning of the fruits under the colour sensor. The other problem happened during testing, the fruit jumped to the next compartment. This problem is caused by the rotor, which is slightly twisted. This issue could be solved by using a more rigid material for the rotor. Figure 4: Frequency reading on Serial Monitor 6. CONCLUSSION There are ways to make the sensor recognised more colours than now. This can be enhanced by programming more RGB values comparison code to allow the system to sort more colour such as yellow, purple, orange and other colour. Another improvement can be made is to make the product use in every industry that need to do colour sorting. This can be improved by expand the size of the product so that it suitable with the product that need to be sort by colour. By applying the idea of this project, industry and agriculture can quickly sort the required product according to their colour. Despite its limitations, this concept can be implemented in various applications with some modifications. We can conclude that time and human effort can be reduced by implementing such projects in the chemical, food, and chip manufacturing industries. There is an existing machine using PIC and other microcontrollers, but there are not many created using Arduino software. By done a lot of testing and experiments, we managed to fix a few errors during the testing process. Before releasing the product, everything should be double-checked to avoid functionality errors. This will not only highlight errors that occur during the development phases, but it will also reduce the extra spending on maintenance. It ensures that the application meets the needs of the customer. It also significantly reduces the risk of failure. The project's reliability can be measured using testing by confirming that the product meets any set technical standard. 91

7. REFERENCES Kunhimohammed C. K, Muhammed Saifudeen K. K, Sahna S, Gokul M. S and Shaeez Usman Abdulla. 2016. Automatic Colour Sorting Machine Using TCS230 Colour Sensor and PIC Microcontroller. International Journal of Research and Innovations in Science and Technology, ISSN 2395-3858, Deepak Devasagayam, Ajinkya Shende, Aldrick Gonsalves, Kaustubh Padalkar, Vinit Rodrigues. 2021. Design and Development of Fruit Sorting and Packaging Machine. https://www.researchgate.net/publication/348231182 Zwinkels, Joanne. 2015. Light, Electromagnetic Spectrum. Encyclopedia of colour science and technology, Business Media New York, doi : 10.1007/978-3-642-27851-8_204-1. Ch.Shravani, G. Indira, V. Appalaraju, 2019. Arduino Based Colour Sorting Machine Using Tcs3200 Colour Sensor. International Journal of Innovative Technology and Exploring Engineering (IJITEE), ISSN: 2278-3075, Volume-8, Issue- 6S4, Neal N. Xiong, Yang Shen, Kangye Yang, Changhoon Lee and Chunxue Wu. 2018. Color sensors and their applications based on real-time color image segmentation for cyber physical systems. https://doi.org/10.1186/s13640-018-0258-x Bresilla K, Perulli GD, Boini A, Morandi B, Corelli Grappadelli L and Manfrini L 2019 Single-Shot Convolution Neural Networks for Real-Time Fruit Detection Within the Tree. Front. Plant Sci. 10:611. doi: 10.3389/fpls.2019.00611 Xiong, N. Shen, Y., Yang, K. et al. 2018 Colour sensors and their applications based on real-time colour image segmentation for cyber physical systems.J Image Video Proc., 23 doi.org/10.1186/s13640- 018-0258-x Leo Louis. 2016. Working principle of arduino and using it as a tool for study and research. International Journal of Control, Automation, Communication and Systems (IJCACS), Vol.1, No.2, April 2016 DOI: 10.5121/ijcacs.2016.1203 Trong Tuan Nguyen, Tat Thang Nguyen, Van Tuu Nguyen, Chi Cong Cao, and Jun Hua. 2018. Application of Arduino Control Mainboard with Colour Light Sensor TCS3200 in Colour Recognition of Edge Banding In Laser Edge Banding Machine doi:10.1088/1755-1315/252/2/022130 Lim Jie Shen, Irda Hassan, 2015. Design and Development of Colour Sorting Robots. EURECA 2014 Special Issue January (2015) 71-81 M. Khojastehnazhand, M. Omid and A. Tabatabaeefar. 2010. Development of a lemon sorting system based on colour and size. ISSN 1996-0824 P. Rajkumar, K. Abinaya, J. Deepa, R. Pandiselvam, C. Indu Rani, S. Parveen. 2021. Development of a farmer-friendly portable colour sorter cum grader for tomatoes DOI: 10.1111/jfpe.13894 Sjaak Wolfert , Lan Ge, Cor Verdouw, Marc-Jeroen Bogaardt. 2017. Big Data in Smart Farming http://dx.doi.org/10.1016/j.agsy.2017.01.023 92

The Development of An Innovative Helmet Dryer Machine Zuhaila Mohammad1 M.Norazizul Fadli Abu Bakar2 and M.Azri Abdul Lateb3 1,2,3 Department of Mechanical Engineering, Politeknik Ibrahim Sultan, Pasir Gudang, 87100, MALAYSIA *Corresponding Author: [email protected] Abstract: Personal Protective Equipment (PPE) is frequently utilized in a range of settings and professions in daily life. Starting with construction labour and moving on to firefighting. The use of motorcycle helmets is one of the many prevalent applications of PPE in daily life. The biggest issue with PPE is humidity, which results from exposure to perspiration and wet weather. The same goes to motorcycle helmets, which are frequently worn. Due to frequent use of the helmet, hygiene issues, contamination, unpleasantness, and bad odour will develop once it becomes wet and moist. Therefore, this project research was undertaken to develop a simple and affordable drying machine to precisely tackle wet and humid motorcycle helmets. Stainless steel was used in the creation of for the primary frame, heating element, and some electronic parts. The efficacy of the dryer machine was then evaluated using the rate at which a wet helmet dried. The designated helmet drier includes an electric fan that is positioned at the base. Through perforations in the stanchion, the electric fan blows air along the interior of the helmet for drying purposes. To provide appropriate, thorough airflow throughout the inside of the helmet, spacers attached to a dome divide the helmet. According to data, a helmet dryer machine can completely dry a wet helmet in less than an hour. It is deemed successful for this project to have produced a high-quality dry PPE for everyday usage. The most important drying characteristic is drying time. Humidity (from sprayed water) doesn't dry out right away. To allow the water molecules to freely travel, they must first be heated. The water molecules must then have enough time to decompose before they may start to absorb moisture from the air. Keywords: Dryer; Humidity; Wet; Bad Odor, Helmet 1. INTRODUCTION A helmet is a piece of safety gear made specifically to shield bikers and riders from harm in the event of an accident. We refer to safety helmets, usually referred to as PPE, as helmets. The PPE is a mandatory use within the construction environment especially when hazards are present (Ronald,2019). In numerous occupations, including law enforcement, firefighting, construction, sports, and aviation crews, safety helmets are worn. Safe helmets are protective equipment used to reduce or prevent the impact on the head when an object is hit or dropped. As an important safety gear, safety helmets can effectively protect the head (D. Ren,2021). It is well known, particularly in Malaysia, that the majority of road users are motorcyclists, followed by drivers of automobiles and a variety of other public transportation. The Malaysian climate can also, to a certain extent, influence how vehicles, whether two- or four-wheeled, are handled. This is owing to Malaysia's location in the Equatorial climate region, which causes the country's climate to experience rain and heat all year. The issue of helmets frequently results in a variety of difficulties, such as theft, getting hit by rain while riding a motorcycle and leaving helmets exposed to rain and heat on the motorcycle after the user exits. Most Malaysians who drive two-wheelers after a rain will unavoidably experience wet and damp helmet problems. Early detection of the development of heat stroke is possible thanks to the ability to forecast how much someone will sweat in a hot environment (Chikage, 2022). Even if this is attributable to their own attitude, certain customers who routinely take such things for granted and have a casual attitude frequently complain when their helmets smell or are moist. Therefore, several methods were taken to address the issue and dry their safety helmets as they rode the motorcycle. 93

1.1 Background/Problem Statement Typically, there is no one right way to dry a helmet. Owners of helmets have in the past discovered they must wait for suitable, hot weather in order to dry their wet or damp helmets. Additionally, Malaysia's unpredictable wet weather contributes to the difficulties in drying the helmet. Due to Malaysia's Khatulistiwa climate, which experiences both heat and rain throughout the year, this issue arises frequently. Motorcycle riders who regularly wear helmets to work or to school will have trouble because of this issue. A helmet that is so wet will be painful on the head and divert attention away from the road ahead to motorcycle riders or passengers. Regardless of the weather, we perspire when we are operating a motorcycle or car on a racetrack. When the heat is exceptionally humid or chilly, the sweat on the helmet does not dry out, which can lead to issues like minimal comfort fogging of the visor, or sweat drops in the eyes. We are also concerned about another issue that motorcycle riders face on extended rides: the sanitation of their helmets. If a wet helmet is not properly dried out once, it will also smell. This happens because the damp helmet lacks ventilation, which allows the interior bacteria to quickly spread and irritate the wearer. Additionally, humidity affects how quickly the Covid-19 virus spreads. In areas with high relative humidity, the aerosol droplet remains in the air for a longer period of time, increasing the risk of infection for more people (Rajeev,2021). Some motorbike riders complained about their musty, damp helmets in interviews. Because the offensive smell makes them feel uneasy as well as scratch their heads. A food delivery person's helmet, for instance, will unavoidably smell because they spend a lot of their daily commute on a motorcycle in the rain and the heat. A helmet that is humid or wet will also be much easy to damage. This is because the interior of the helmet was made of a material that resembles a sponge, which easily absorbs moisture. It is essential to stay dry in order to retain quality and durability. Wet and damp helmets constitute a serious problem since they may obstruct daily tasks. Wet and damp helmets are a major problem since they could obstruct daily activities. The problem of uncomfortable clothing cannot be disregarded. The majority of people who use helmets do not like having to flush a damp helmet and wait for it to dry in order to have a comfortable helmet. 1.2 Research Scope The design idea is only focused on the helmet drying scope based on: i. Small size for portability ii. Use heating filament as a heating medium iii. Closed space to allow hot air circulation 2.0 LITERATURE REVIEW In fact, dryers are already on the market that are used to dry various wet and damp clothes and equipment. Even so, technically there are no helmet dryers in Malaysia yet. In relation to that, this project tries to find ideas from existing dryers and innovates a special dryer for helmets. Design is next step where the purpose is to develop an appropriate instructional method to achieve the objective. SWOT analyses were used to provide a complete picture of a product, according to Simone Somekh in 2022. This project applied the analysis on several products in order to find idea in designing a new innovative helmet from existing related product. 94

Table 1: SWOT Analysis, Comparison of Dryer Products Product ‘Pengering Helm’ Stilo Helmet Dryer Pronomar Drying Cabinet Item Strength - Low cost - Easy to operate - Save space - Mobile - Besides helmet, able to dry up shoes and socks - Able to dry up a variety and a large amount of equipment. - Heating and drying thoroughly due to hot air circulation Weakness have maintenance - replacement of LPG barrels that have run out High price for a simple task; price > RM800.00 Use a lot of space Opportunit y heating is only concentrated from inside the helmet. Hot air circulation will provide thorough heating and drying if having a close area heating is only concentrated from inside the helmet. Hot air circulation will provide thorough heating and drying if having a close area Suitable usage in industry field Threats the danger of using LPG as a heating medium Not suitable for personal usage Reference https://www.lazada.co.id/tag/pen gering-helm/ https://www.nickygrist.com/stilohelmet-and-equipment-dryer https://www.pronomar.com/dryin gsystems/ Due to the employment of heating filament, the Pronomar Drying Cabinet and Stilo Helmet Dryer offer advantages in terms of heating medium. The equipment is dried using the hot air that has resulted. Unlike the "Helm Dryer," which needs to have its LPG tank replaced if it runs out, only electricity is needed. In comparison to comparable products, the Stilo Helmet Dryer provides advantages in terms of space and portability. A contained chamber that allows for hot air circulation gives the Pronomar Drying Cabinet an edge in terms of thorough drying, nevertheless. In contrast to the "Helm Dryer" and Stil Helmer Dryer, just the interior of the equipment being dried is concentrated during drying. 3.0 METHODOLOGY The ADDIE model was chosen as a guide for the procedures involved in this project since it is a straightforward problem-based innovation initiative. Due to its conceptual framework being pertinent to the standard of learning and the quality of Design and Technology disciplines, the ADDIE model is regarded as the most appropriate methodology concept (Zamri Sahaat et al., 2019). The process utilized to conduct this study is briefly described below. Figure 1: Project Methodology Based on ADDIE Model 3.1 Problem Identification Using Questionnaires Targeted participants were asked questions to identify areas that needed improvement and to highlight areas of concern. Before the studies began, each volunteer participant the study gave their consent. The design of the questionnaire uses a quantitative methodology to make it easy to summarize, compare, and generalize the findings. Likert-style questions, in which respondents had to select from a list of five to ten answers, were used in the majority of these surveys, according to Satyendra,2020. Surveys, social science research, and ANALYSIS • Problem identification •Questionnaire DESIGN • Define learning objective & instructional strategies • Product Design evaluation using SWOT analysis DEVELOPMENT • Develop & validate the learning resources • Product Fabrication IMPLEMENTATION • Prepare the learning environment & implement the learning solution • Product testing EVALUATION • Assess the effectiveness of the course instruction • Analysis and discussion Drying Process Analysis 95

health status all frequently employ the Likert scale. Ten motorbike riders provided their answers to this quiz. The questionnaire was divided into sections for participant age, helmet usage style, and opinion on damp or humid helmets. The average scale was determined using Eq. 1 to find the minimum or maximum scale of the 5-point and 10- point type scales. The range of the average scale was established to be 1 to 1.80, which represents strongly disagree, 1.81 until 2.60, which represents do not agree, 2.61 until 3.40, which represents (somewhat) agree, 3.41 until 4.20, and 4.21 until 5.00, which represents highly agree (Beglar,2014) Average scale = (the number of respondents chosen,n)x(response weighting,n) sum of all respondents Eq.1 Over the course of the project, several discoveries were made. It should stress the examination of the entire project as one component of it. As a result, a crucial concept like system operation might be described as operating according to plan. Either the operating system or the fully functional project can be used for this project. 3.1.1 Data collection and analysis using questionnaires among helmet users The surveys were completed by ten people. The participants were divided into three age groups: 10-16 years old, 17-30 years old, 31-50 years old, and 51 years and older. Table 2: Responder age 10-16 ages 17-30 ages 31-50 ages 51 ages 1 2 6 1 Table 3: Types of user’s helmet Open face helmet Full-face helmet Modular helmet Half cut helmets Off-road helmet 4 6 0 0 0 Based on the questionnaire results, the average scale for the majority of the questions found that it is at the highest level of strongly agree with a range of 4.3 to 4.8. Except for the question wet helmets emitting foul odours, the average score was 4.21. With an average scale of 4.7, 8 out of 10 respondents strongly agree that there is a product that can dry the helmet faster and more practical to overcome the problems they face when the helmet is damp. Table 4: Helmet User Responses Question/ scale 1 2 3 4 5 Average scale Do you feel more self-assured when wearing a cosy (dry) helmet 7 3 4.3 Do you agree wet helmets emit foul odours? 1 7 2 4.1 Do you think a device should exist to help you dry your helmet more rapidly, especially during the rainy season? 1 1 8 4.7 When the heat is especially humid, does the sweat on the helmet not dry up, causing issues like uncomfortable sweat drops in the eyes or visor fogging? 1 5 5 4.8 Malaysia's unpredictable wet weather contributes to the difficulties in drying the helmet? 2 8 4.8 96

2.2 Design using AutoCAD. Figure 2: Design of Innovative Helmet Dryer Machine 2.3 Development: Product Fabrication Based on the created engineering drawing, the helmet dryer was fabricated. A close main frame was developed initially from mild steel plate and glass through grinding, drilling, welding, rebating process. Next was the development of a circuit board that used to control the heating which contain heating filament, air blower, rocker switch, timer switch, temperature controller and sensor. Lastly, they were assembled accordingly, and the outcome as illustrate in figure below. Figure 3: Final Product of Innovative Helmet Dryer 450.00 20.00 600.00 DRAWN LENOVO CHECKED QA MFG 25/3/2019 TITLE APPROVED SIZE A4 SCALE 1 / 10 DWG NO perf 250.00 450.00 250.00 100.00 130.00 700.00 97

Figure 4: Flowchart in developing the Helmet Dryer Machine 2.4 Implementation and Evaluation: Drying Process Analysis The drying works analysis is performed by setting water quantities of 20ml, 40ml, and 60ml. Water is then sprayed into the selected helmet model using a bottle of water sprayer into which a quantity of measured water has been inserted. This method is used as an example of a simulation of the actual rainfall that is occurring. After the water is sprayed into the helmet, the weight of the helmet that stirs the water is weighed in order to identify a damp cap mass. Finally, the damp cap is inserted into the 'Drying Machine,' and the drying time is calculated. As shown in tables 5 and 6. Table 5: Shows the drying rate(time) versus volume for an open-face helmet (model MS88) Open Face Helmet (Model Ms88 900g) Volume (ml) Weight Time (minutes) 20ml 40ml 60ml 20g 40g 60g Trial 1 20 minutes 30 minutes 60 minutes Trial 2 20 minutes 32 minutes 61 minutes Trial 3 20 minutes 30 minutes 60 minutes Trial 4 20 minutes 31 minutes 62 minutes Trial 5 20 minutes 32 minutes 61 minutes AVERAGE 20 minutes 31 minutes 61 minutes Start Research Title Selection Making A Project Sketch Identify Problems of Project Scope and Objectives Identify the Components to be Used Created Engineering Drawing using AutoCAD Fabricated NO Demonstration Development of a Circuit Board Drying Process Analysis YES 98

Table 6: Shows the drying rate(time) versus volume for Full face helmet (model MHR III) Full face helmet (MODEL MHR III 700g) Figure 5: Graph Sprayed Water Vs Drying Time Figure 5, briefly show the average of drying time according to quantity of water sprayed onto both of open face helmet and full-face helmet. The full-face helmet line shows a uniform drying rate against the increase in the amount of water sprayed. Although there is a slight decrease in the open face line, the degree of drying also increases along with the increase in the quantity of water sprayed. 4.0 CONCLUSION Overall, the machine produced positive results when all drying time findings were controlled, indicating that it met the project's objectives and scope. Analysis data shows the drying time period is between 20 minutes and 61minutes for Open Face Helmet (Model Ms88 900g) and for Full face helmet (MODEL MHR III 700g) data shows the drying time period is between 15 minutes-51 minutes based on the rate of water integration in the helmet. This implies that the project of creating a Helmet Dryer Machine is a correct and functional concept. When gathering analytical data, two helmet models with three different humidity levels are used. Water sprayed into the helmet in quantities of 20ml, 40ml, and 60ml was used for the analysis. As a result, the process of gathering data can be completed more quickly and with greater accuracy. For less than 1 hour, people can wear back their wet and humid helmet after using this innovative helmet dryer machine. 1 2 3 open face 20 31 61 full face 15 32 51 20 31 61 15 32 51 0 10 20 30 40 50 60 70 Time (minute) water spayed (g) Sprayed water vs drying time Volume (ml) Weight Time (minutes) 20ml 40ml 60ml 20g 40g 60g Trial 1 15 minutes 35 minutes 55 minutes Trial 2 16 minutes 34 minutes 50 minutes Trial 3 14 minutes 30 minutes 50 minutes Trial 4 15 minutes 31 minutes 51 minutes Trial 5 15 minutes 30 minutes 50 minutes AVERAGE 15 minutes 32 minutes 51 minutes 99

5. REFERENCES Chikage Nagano, Riho Tanaka, Kimiyo Mori, Kimie Fukuzawa, Seichi Horie. 2022. Helmet-type measuring device for estimating the amount of sweating in a hot environment,Safety and Health at Work,Volume 13, Supplement,Page S272. D. Ren, T. Sun, C. Yu and C. Zhou. 2021 "Research on Safety Helmet Detection for Construction Site," 2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI), 2021, pp. 186-189, doi: 10.1109/CISAI54367.2021.00042. Rajeev Jayadevan1 , Raveendran AV. 2021 The Humidity Hypothesis Of COVID-19 Spread, BMH Med. J.2021;8(1):5-7. Special Article Satyendra Nath Chakrabartty. 2020 Transforming Likert Scores to Ratio Scale, Romanian Journal of Psychological Studies Hyperion University Ronald Valledor Gomeseria,2019 Personal Protective Equipment (PPE) Planning in the Construction Environment,DOI 10.17605/OSF.IO/VQ4CK Beglar, D., & Nemoto, T. (2014). Developing Likert-scale questionnaires. JALT2013, Conference Proceedings, 1–8. Zamri Sahaat et. al. (2020) ADDIE Model in Teaching Module Design Process Using Modula Method: Applied Topics in Design and Technology Subjects. DOI:10.2991/assehr.k.200824.161. Conference: 1st Progress in Social Science, Humanities and Education Research Symposium (PSSHERS 2019). Simone Semokh (2022), SWOT Analysis of A Product And What Can You Use It For? ‘Pengering Helm’ (2022). The product was cited from https://www.lazada.co.id/tag/pengering-helm/ on February 2022. Stilo Helmet Dryer (2022), The product was cited from https://www.nickygrist.com/stilo-helmet-andequipment-dryer on Febuary 2022. Pronomar Cabinet Dryer (2022). The product was cited from https://www.pronomar.com/dryingsystems/ on March 2022 100

Design of Mini Plasma Reactor for Toxic and Hazardous Waste Destroyers using a Plasma Arc Cutting Machine Royas Putra1 , Aulia2 , and Yona Mayura3 1 Andalas University Department of Electrical Engineering, St. Limau Manis, Padang, 25163, INDONESIA 2 Andalas University Department of Electrical Engineering, St. Limau Manis, Padang, 25163, INDONESIA 3 Politeknik Negeri Padang Department of Electrical Engineering, St. Limau Manis, Padang, 25164, INDONESIA *Corresponding Author: [email protected] Abstract: The growing population of local and urban communities has increased the quantum of toxic and hazardous waste, which has become a complex task for the municipal authorities. From statistical observations, it can be seen that the ability to manage waste and waste production is not balanced. This is due to the limited means of collection, transportation, disposal, and final destruction of waste. In addition, current waste processing methods still contain hazardous elements and still have shortcomings, namely in the environmental and health sectors as well as for the socioeconomic and cultural life of the community. Waste to energy technologies is emerging that has the potential to create renewable energy from waste. The latest technology is proposed which in the future is expected to be the best solution in dealing with the waste problem, namely the use of plasma technology or plasma gasification. Plasma gasification technology can decompose various toxic compounds within 1/1,000 seconds, it can eliminate the process of formation of other compounds and the formation of toxic gases that usually occur in combustion from an incinerator. The focus of this research is to develop and design a high-temperature mini plasma reactor, apply effective and efficient toxic and hazardous waste treatment methods, and measure flow parameters, air pressure, and their effect on waste decomposition time. Through several tests, it was concluded that the mini plasma reactor was designed to withstand heat up to 1300C. The electrical system uses the power source of the 220 Volt PLN which is connected to the plasma arc cutting machine. The results showed that the higher the current and air pressure, the plasma flame burst will get longer and hotter. This affects the time in the decomposition of the toxic and hazardous waste following the capabilities of the mini plasma reactor. Keywords: Reactor, Toxic and Hazardous Waste, Waste to Energy, Plasma Gasification, Plasma Arc Cutting. 1. INTRODUCTION The waste problem factor is strongly influenced by the population, socio-economic conditions of the community, and technological advances. With the increasing number of residents, limited landfill or land, bad community behavior, which still does not realize the importance of the environment, and is accompanied by consumptive patterns of the community itself, and will indirectly have an impact on increasing the rate of waste production, type, volume, and the amount of waste generated is not commensurate with the handling process. Waste problems, if not handled properly, will cause many problems and risks, such to human health and other living things [1]. The increasing amount of industrial and residential waste and its environmental footprint dictates the need for effective waste management practices. Thermal waste treatment technology plays an important role in energy recovery from waste. Conventional and plasma gasification is an advanced thermal processing technology that has been introduced as a promising and environmentally friendly way for energy utilization from biomass and municipal solid waste (MSW) [2]. Some of the methods of processing waste that are widely used today are: 1. Composting and hoarding reducing the volume of waste by retrieving fresh organic materials that can be composted and recycled materials that can be reprocessed. The rest will then be stockpiled, the problems that will be faced due to the hoarding are soil degradation, polluted groundwater, and vulnerability to landslides. 101

2. Combustion (Incineration) is the burning of waste that is carried out in full oxidation in an incinerator. Where the incineration process uses fossil fuels which will leave ash and may still contain harmful elements. 3. Pyrolysis is the conversion of materials into liquid, solid and gaseous fractions by heating in the absence of air. This is a way of thermal degradation in a reactor, where a useful byproduct of pyrolysis is charcoal. This also leaves ash which contains harmful elements [3]. Waste to energy technologies has the potential to create renewable energy from waste, including municipal solid waste, industrial waste, agricultural waste, and waste by-products. The main categories of waste-toenergy technologies are physical technologies, which process waste to make it more useful as a fuel, thermal technologies that can generate heat, fuel oil, or synthetic gas from organic and inorganic waste, and biological technologies in which bacterial fermentation is used to digest organic waste to produce fuel [4]. The utilization of plasma gasification, and waste into energy (WtE) is one of the new technologies introduced several decades ago. In this case, the plasma arc makes a carbon-based part of the waste material such as municipal solid waste, sludge, agricultural waste, etc., and produces a synthetic gas that can be used to generate energy through reciprocating engine generators, gas turbines, and boilers [5]. 2. LITERATURE REVIEW 2.1 Toxic and Hazardous Waste Toxic and hazardous waste is the residue of an activity or business that contains toxic and hazardous materials which due to their quantity, nature or concentration, either directly or indirectly, can harm, pollute and damage the environment, health and survival of humans and other life [6]. The packaging, storage, collection, management and transportation of Toxic and hazardous waste must be carried out in a manner that is safe for work, society and the environment. An important factor related to this safety is the marking on the places for storage, collection, and processing as well as on every packaging and vehicle for transporting toxic and hazardous waste. This is intended to provide the identity of the waste so that the presence of toxic and hazardous waste in a place can be recognized. toxic and hazardous waste is marked with the symbol, it can be easier to find out basic information regarding the type and nature or characteristics of toxic and hazardous waste for people carrying out work, for toxic and hazardous waste treatment supervisors and people around them. Because it is very important and useful to trace and determine the safe treatment of toxic and hazardous waste [7]. Figure 1: Toxic and Hazardous Waste Symbols [6] Each symbol shown in Fig. 1 is a specific image to indicate the characteristics of toxic and hazardous waste. There are 8 (eight) types of symbols, namely: 1. Explosive toxic and hazardous waste classification symbol 2. Corrosive toxic and hazardous waste classification symbol 3. Combustible solid symbol 4. Flammable liquid symbol 5. Reactive toxic and hazardous waste classification symbol 6. Reactive and hazardous waste classification symbol 7. Toxic and hazardous classification symbol causes infection 8. Mixed classification B3 waste symbol Integrated waste management (IWM) is the application of a combination of waste management practices to minimize the health and environmental impact of waste disposal. IWM planning evaluates local needs and conditions to select the most appropriate management practices to create a comprehensive system. IWM planning has identified four main practices. These include source reduction, which focuses on reducing the amount and toxicity of waste generated; material recovery, which includes diversion practices of recycling and 102

composting; energy recovery, which includes energy production from landfill gas, anaerobic digestion, incineration, or gasification; and disposal, which is most commonly accomplished by landfilling [8]. Then these practices are organized into a hierarchical model that provides strategies according to environmental impacts as illustrated in Figure 2. Figure 2: Diagram of Integrated Waste Management Systems [6] 2.2 Waste to Energy Waste to energy is the process of generating energy in the form of heart or electricity from waste, just as power plants use oil, coal, or natural gas. The burning waste heats water into steam. It drives a turbine to produce electricity. Waste to energy technologies can be used to produce biogas (methane CH4 and carbon dioxide Co2), synthetic gas (hydrogen and carbon monoxide), liquid biofuels (ethanol and biodiesel), or pure hydrogen, this fuel which can then be converted into electricity. The main categories of technologies used for the conversion of waste into energy are physical methods, thermal methods, and biological or biochemical methods [4]. 2.3 Conventional Gasification Gasification uses a thermal process to capture chemical energy from feedstocks. There are three main classifications of gasification processes, characterized by the reactor temperature [8]. Pyrolysis occurs at lower temperatures between 500°C and 800°C and its distinguishing characteristic ar that feedstock is processed in the absence of oxygen. Conventional gasification is thermal processing at temperatures between 550°C and 1600°C [9]. Plasma-assisted gasification or plasma arc gasification uses a plasma field of electrically charged gas to reach temperatures of 4,000°C to 7,000°C. At these high temperatures, plasma arc systems experience more feedstock flexibility, achieve higher thermal efficiencies, and produce cleaner syngas [8]. Some conventional gasification systems require the effluent to be preprocessed to achieve more even heating of the feedstock and higher conversion efficiency. Prepared residual derived fuel (RDF) enters the conversion chamber where it is heated to release synthesis gas, which is primarily composed of carbon monoxide and hydrogen. These syngas is cooled and cleaned before being converted into liquid fuels or combusted to produce electricity and heat [8]. The gasification process diagram is shown in Fig. 3. Figure 3: Diagram of Conventional Waste Gasification System [8] 103

2.4 Pyrolysis Pyrolysis takes place at lower temperatures in the absence of oxygen and produces intermediate products of syngas, pyrolysis oil, and char [8]. Syngas from pyrolysis contains methane, as well as carbon monoxide, hydrogen, carbon dioxide and water [9]. Two main types of pyrolysis processes are slow pyrolysis and flash pyrolysis. Slow pyrolysis takes place in a stationary reactor and is used to maximize the production of gas and solid byproducts. Flash pyrolysis occurs over several minutes and is used primarily for producing pyrolysis oils [10]. 2.5 Plasma Arc Gasification Plasma arc gasification is the newest development in waste gasification technology. The plasma field reaches temperatures up to 14,000°C [8]. These extremely high temperatures break down waste more completely giving plasma gasification systems increased feedstock tolerance and higher syngas yields than traditional gasification while producing less char and tar [9]. Application of plasma torch provides a high level of temperature of the process and allows destroying the toxic compounds, formed in the traditional waste incineration [11]. Fig. 4 shows a schematic of the experimental installation for MSW plasma gasification. Figure 4: Scheme of The Experimental Installation for Plasma Gasification of MSW [11]. Plasma arc cutting (PAC) is a thermal cutting process that makes use of a constricted jet of high-temperature plasma gas to melt and separate (cut) metal [12], in Fig. 5 there is a schematic diagram of plasma arc cutting the basic principle of plasma arc cutting is to use electricity to heat the air very high up to the plasma point. In the working process of the plasma cutting machine, an inverted gas is blown at high speed from the nozzle, and at the same time, an electric arc is formed through the gas from the nozzle to the surface [13]. The operation of the plasma cutting machine begins with the contact between the electrodes touching the nozzle, when the cutting torch is turned on, DC current flows through this process, then hot air presses and starts trying to come out simultaneously from the tip of the nozzle, then the compressor pushes the used air out of the nozzle. Air flows and establishes the gap between the electrode and the tip, the transformer automatically increases the voltage to maintain a steady and constant current, the electric current then heats up and heat becomes plasma. Figure 5: Schematic Diagram of Plasma Arc Cutting Explanation: (1) MSW Gasification Zone. (2). Pipe for Supplying Briquette MSW. (3) Reactor. (4) Arc Plasma Torch. (5) Plasma Flame. (6) Flue Gas Cooling Unit. (7) Gas Purification Unit With A Bag Filter. (8) Gas Sampling System for Analysis. (9) Exhaust System. (10) Slag Formation Zone 104

The main advantages of thermal plasma are the high densities and high temperature that allow high heat and reactant transfer rate, the smaller size of the installation, and rapid start-up and shut down. The use of electricity as input is also very interesting as it decouples the heat generation from the oxygen potential, thus allowing for better control of the processing unit. Plasma can be either generated by DC electric discharges, RF and microwave discharges. For the treatment of waste, plasma is preferentially generated by DC electric discharge. For that, two kinds of devices can be used: transferred and non-transferred arc [14]. 3. DESIGN METHODOLOGY In this research, a mini plasma reactor for destroying waste with a capacity of 500 grams will be designed. The supporting tools used consist of the main reactor, transformer/plasma cutting machine, voltage regulator, high voltage cable, compressor, electrodes, nozzle, mass pliers, digital thermocouple, plasma torch, refractory cement insulation, glass, chimney, iron pipes, valves and other supporting tools. 3.1 Mini Plasma Reactor Design Description The design specifications for the Mini Plasma Reactor as shown in Fig. 6 are as follows: 1. Height of reactor 75 cm, the outer diameter of the reactor 28 cm, the inner diameter of the reactor 20 cm 2. Monitor window 30 cm high, 10 cm wide 3. Iron pipe 10 cm long, 5 cm diameter 4. Insulation thickness 5 cm 5. Insulation using fire-resistant cement Technocast Castable TNC-12 max temperature 1500°C (a) (b) (c) Figure 6: Mini Plasma Reactor Design (a) Top View, (b) Front View, (c) Back View Design of mini plasma reactor is also added with monitoring window, as shown in Fig. 7. Figure 7. Mini Plasma Reactor Design of The Monitoring Window The main source of 220 Volt electricity supply is connected to a circuit breaker and a socket. The output goes directly to the electric voltage regulator circuit, namely the sliding regulator before being connected to the 105

compressor and voltage transformer or plasma cutting machine. Connecting to the reactor to create plasma is done by modifying the reactor, a small hole is made in the iron or workpiece which is connected to the positive output terminal of the plasma cutting machine, and a portable connecting iron is made which is connected to the nozzle to trigger the plasma reaction at the desired place. It follows the diagrams, designs and schematics shown in Fig. 8 below. The tools used to create this plasma are: 1. Transformer / Plasma cutting machine It serves to increase the input voltage from the inverter to reach the plasma voltage. Plasma cutting is a machine that functions to melt or cut objects such as iron 2. Voltage regulator It is useful as a regulator of the output voltage of the PLN electricity before entering the plasma cutting machine so that it can regulate the formation of a plasma in the plasma reactor. 3. Voltage cables and sockets They connect the input and output of the plasma arc cutting machine with a plasma reactor that is capable of transmitting 220 Volt voltage to connect electricity between the Plasma Cutting Machine with a voltage regulator. 4. Compressor It Serves to produce plasma in the arc, supply heat and increase pressure or get air from the surroundings which will then be pressurized in the tube, then redistributed as compressed air. (a) Plasma Power Generation Schematic Diagram (b) Plasma Power Generation Schematic Design (c) Plasma Trigger Schematic Figure 8: Plasma Power Generation Designs and Schematics 106

4. RESULTS AND DISCUSSION (a) (b) Figure 9: (a) Plasma Form (b) Decomposition Process The mini plasma reactor has been made is tested. These tests consisted of leakage tests and plasma tests. The reactor is suitable and ready for use, then observations and data collection are carried out which are then analyzed. In Fig. 9 there is a plasma form and the decomposition process. The display of temperature data obtained is shown in figure 10, the instrument testing was carried out in the high voltage engineering laboratory of Andalas University. The data obtained is then processed using Microsoft Excel to see the effect of the data comparison chart from each test. Furthermore, the data is processed using Design Expert 12 software with the response surface methodology. Figure 10: Display of Temperature Data on Testing 107

4.1 Research Data Description In this research observation data from the object being tested were analyzed. The data was obtained by conducting various experiments with various conditions directly in the high-voltage laboratory of Andalas University. With the data obtained are shown in Table 1 and Fig.11, as follows: Table 1: Recapitulation of Testing Data on Equipment in The High Voltage Laboratory of Andalas University Parameters Testing 1 Testing 2 Testing 3 Volt Electricity (V) 220 220 220 Current (A) 10 15 20 Air Pressure (MPa-kgf/cm2) 3 4 5 Waste (gram) 500 500 500 Decomposition Time (minute) 9 7 6 Temperature (0C) 1139 1236 1260 Figure 11: A Data Comparison Chart Was Obtained by Experiments To get the temperature and time of decomposition, several experiments were carried out by varying the current and air pressure. The results showed that the higher the current and air pressure, the plasma flame burst will get longer and hotter. This affects the time in the decomposition of the waste following the capabilities of the mini plasma reactor. In the data comparison chart, it can be seen that the fastest decomposition time is 6 minutes, and 9 minutes is the longest. While the highest temperature is 1260°C and 1139°C is the lowest temperature in the test. -100 100 300 500 700 900 1100 1300 0 200 400 600 800 1000 1200 1400 A Data Comparison Chart Testing 1 Testing 2 Testing 3 108

4.2 Design Expert 12 Design Expert 12 software uses response surface methodology with a model of central composite design. There are two process parameters selected as factors (the amount of current and air pressure) determining the high and low values of the designed factors. This design can provide information about effects, interactions, and predictions. After inputting the level factor data (high and low), the design expert 12 software will read and display the data. Optimization of the data in this research using design expert 12 is shown in the following Table 2. Table 2: The Amount of Current, Air Pressure and Response Time Num Std Run Factor 1 A: Current Amp Factor 2 B: Pressure Mpakgf/ Response 1 Time Minute 1. 6 1 22.0711 4 6 2, 2 2 20 3 7 3, 5 3 7.92893 4 8 4. 7 4 15 2.58579 9 5. 8 5 15 5.41421 6 6. 10 6 15 4 7 7. 3 7 10 5 8 8. 4 8 20 5 6 9. 9 9 15 4 7 10. 1 10 10 3 9 Fig 12 show the time prediction points when running 1, according to the data in table 2, the current value is 22.0711 and the air pressure is 4 MPa, so it gets a response time of 6 minutes The results obtained are very effective and efficient in obtaining optimum conditions that are close to real conditions. (a) (b) Figure 12: (a) Contour Design Expert, (b) Design Expert of 3D Surface 109

4.3 Discussion The problem of solid waste continues to be discussed, because it is directly related to the lifestyle and culture of the community itself. Waste problems, if not handled properly, will cause many problems and risks, such to human health and other living things [1]. The ever-increasing amount of industrial and residential waste and its environmental footprint dictates the need for effective waste management practices. For this reason, the latest technology is proposed which in the future is expected to be the best solution in dealing with the waste problem, namely the use of plasma technology, or better known as plasma gasification. The utilization of plasma gas, waste into energy (WTE) is one of the new technologies introduced several decades ago. In this case, the plasma arc can produce synthetic gas which can be used to generate energy through reciprocating engine generators, gas turbines, and boilers [5]. Therefore, the authors develop and design a high-temperature mini plasma furnace, so that it can apply an effective and efficient waste treatment method. with the test results, namely: to get the temperature and time of decomposition, several experiments were carried out by varying the air current and pressure, from the experiments carried out it was seen that the higher the current and air pressure values, the longer and hotter the plasma flame bursts. This affects the time in the decomposition of waste in accordance with the capabilities of the tool. The fastest decomposition time is 6 minutes, and 9 minutes is the longest. While the highest temperature is 1260°C and 1139°C is the lowest temperature in the test. because of the limitations of the author in researching, the suggestions for further researchers, in order to be able to conduct data collection or research on data variables that have not been obtained. In order to be able to complete the next tool to be able to develop the results of the decomposition reaction in the form of flue gas for sample analysis or be processed as a source of electricity generation. 5. CONCLUSIONS This research is expected to help understand and develop or analyze mini plasma gasification technology in the future. This research can also be used as a reference to get the quality of effective and efficient waste management that can overcome the toxic and hazardous waste problem. Through several tests, it was concluded that the mini plasma reactor was designed to withstand heat up to 1300C. The electrical system uses the power source of the 220 Volt PLN which is connected to the plasma arc cutting machine. The results showed that the higher the current and air pressure, the plasma flame burst will get longer and hotter. This affects the time in the decomposition of the toxic and hazardous waste following the capabilities of the mini plasma reactor. 6. ACKNOWLEDGEMENT The author would like to thank all parties who have been involved in this research. 7. REFERENCES [1] M. Rizal, “Analisis Pengolahan Persampahan Perkotaan (Studi Kasus pada Kelurahan Boya Kecamatan Banawa Kabupaten Donggala),” Jurnal SMARTek, Vol. 9, 2011. [2] M. S. Lavaee, “Waste to Energy (WTE): Conventional and Plasma-assisted Gasification Experimental and Modeling Studies,” A Thesis presented to the University of Waterloo, Ontario, Canada, 2013. [3] S.D.S.Djaja, Penerapan Teknologi Plasma pada Pemusnahan Sampah Kota, Metallurgist-ITB74- Inkubator, 2010 [4] J. Sanderson, "Waste to Energy," Proceedings of the Royal Society of Victoria, 2014. [5] M. Pourali, “Application of Plasma Gasification Technology in Waste to Energy Challenges and Opportunities,” IEEE, vol.1, no.3, pp.125-130, 2010. [6] Indonesia, “Peraturan Pemerintah No. 85 Tahun 1999 tentang Perubahan Atas Peraturan Pemerintah No. 18 Tahun 1999 tentang Pengelolaan Limbah Bahan Berbahaya”, 1999. [7] L.E. Sunarsih, “Penanggulangan Limbah,” Deepublish, Yogyakarta, 2017. [8] K. Hervin, “Feasibility Analysis of Gasification for Energy Recovery from Residual Solid Waste in Humboldt County”, A Thesis presented to the University of Humboldt State University, Berlin, Germany, 2013. 110

[9] U. Arena, “Process and technological aspects of municipal solid waste gasification. A review,” Waste Management., vol. 32, no. 4, pp. 625–639, 2012. [10] F. Lamers, E. Fleck, L. Pelloni, and B. Kamuk, “Alternative Waste Conversion Technologies,” ISWA - International Solid Waste Association, p. 35, 2013. [11] V. E. Messerle, A. L. Mosse, and A. B. Ustimenko, “Municipal Solid Waste Plasma Processing : Thermodynamic Computation and Experiment,” IEEE Transactions on Plasma Science, pp. 1–6, 2016. [12] S. Ali, D. K. Prasad, S. Shankar, and K. Saw, “Experimental Investigation of Temperature Distribution and Surface Roughness for Cutting Aluminium-19000 and Stainless Steel 304 Using Plasma Arc,” International Journal of Advanced Technology in Engineering and Science, vol. 4, no. 3, pp. 344–349, 2016. [13] S. Chamarthi, N. S. Reddy, M. K. Elipey, and D. V. R. Reddy, “Investigation analysis of plasma arc cutting parameters on the unevenness surface of hardox-400 material,” Procedia Engineering, vol. 64, pp. 854–861, 2013. [14] C. Ducharme, N. J. Themelis, and M. J. Castaldi, “Technical and economic analysis of Plasma-assisted Waste to Energy processes,” A Thesis presented to the University of Columbia, New York, USA, 2010. 111

Mixed Durability Performance Asphalt Concrete – Wearing Course (Ac-Wc) Using Lime Ash as Filler Substitution Lusyana1 , Mukhlis2 , Ernita Suardi3 , Alfino Busri4 And Ghina Pujadany5 1,2,3,4,5 Civil Engineering, Padang State Polytechnic, Padang, 25164, WEST SUMATERA *Corresponding Author: [email protected] Abstract: Road is a means of transportation of Asphalt Concrete Wearing (AC-WC) as a wearing course (wearing course) is a pavement layer that is directly related to the load and weather, then the layer must have the ability to be weather-resistant, water-resistant, and have good Coarseness. hinted. Usually the filler used in an asphalt mixture is obtained from rock ash. However, in the field conditions, rock ash filler has limited availability, so one type of substitute material that is possible is lime ash. With a mixture of fillers or fillers that utilize lime ash to function as a cavity filler and asphalt concrete binder, it is expected to increase the density, durability and stability of the pavement mixture using the Marshall Immersion (MI) method. It is hoped that the replacement of the filler material can increase the density, durability and stability of the pavement mixture. The results of the AC-WC mixture test with the addition of 0%, 5%, 10%, and 12.5% lime ash with an asphalt content of 5% to 7% obtained the optimum asphalt content value using the Marshall method of 5.99% at 0% variation of the addition of lime ash, 6 ,31% in the 5% variation of the addition of lime ash, 6.57% in the 10% variation of the addition of lime ash and 6.60% in the 12.5% variation of the addition of lime ash. Based on the results of the study, the value of marshal immersion tends to increase with increasing lime ash. The mixture with lime ash 12.5% gave better durability performance (99.60%) compared to lime ash 0%, 5% and 10% (97.52%, 97.82%, and 99.39%). Keywords: Durability, AC-WC, Asphalt, KAO, Marshall Immersion, Lime Ash. 1. INTRODUCTION 1.1 Background Road pavement is one or several layers of material that is compacted on the subgrade so that traffic can run smoothly without being hampered. As time goes by and the increase in population is directly proportional to the increase in the volume of vehicles, making road pavements, especially flexible pavements, will experience faster damage. Road pavement, especially flexible pavement. has weaknesses, especially in the pavement layer, such as experiencing deformation (change in shape) due to excessive vehicle loads, and cracks caused by changes in temperature which will cause potholes over time. The development of traffic that continues to increase has led to increased demands for transportation infrastructure. Road is a medium of transportation. The media is used as the movement of traffic on land areas which include the media for the passage of motorized vehicles, which are on the surface or below the ground surface of the cable.(Minister of Transportation of the Republic of Indonesia, 2006). Asphalt Concrete Wearing Course(AC-WC) is a mixture of continuously graded aggregate with a binder of asphalt. Asphalt Concrete Wearing (AC-WC) as a wear layer (wearing course) is a pavement layer that is directly related to the load and weather, then the layer must have the ability to be weather-resistant, waterresistant, and have the required Coarseness. However, in the existing road construction, especially on the wearing course, there are still many damages that reduce the level of road service, one of which is puddles of water on the asphalt which causes damage. Mixture damage to water in the pavement layer, so that it changes shape like a hole. The strength of AC-WC comes from the interlocking between asphalt with aggregate and filler.(Mahli, 2017). Usually the filler used in an asphalt mixture is obtained from rock ash. However, in the field conditions, rock ash filler has limited availability, so one type of substitute material that is possible is lime ash. According to Refi(2019)In general, lime is hydraulic, does not show weathering and can be carried by currents. Physically, limestone is a sedimentary rock consisting of the mineral "Calcium Carbonate" (CaCO3) which is then heated at high temperatures and then doused with water to produce "Calcium Hydroxide" (Ca(OH)2) 112

extinguished lime. With a mixture of fillers or fillers that utilize lime ash to function as a cavity filler and asphalt concrete binder, it is expected to increase the density, durability and stability of the pavement mixture using the Marshall Immersion (MI) method. This research is expected to be able to provide solutions to problems in the community, namely lime ash waste that has accumulated and has not been utilized, which is expected to improve the quality of asphalt mixtures, especially those that can be used for public roads. 1.2 Research purposes The aims of this research are as follows: 1. Obtaining Marshall's Optimum Asphalt content value on a mixture of Asphalt Concrete – Wearing Course (AC-WC) wear layer without using a mixture of rock ash filler (0%) and using a mixture of lime ash filler with variations (5%; 10%; 12,5). 2. Obtain residual strength (IKS) in the mixture of Asphalt Concrete Wearing Course (AC-WC) without using a mixture of rock ash filler (0%) and using a mixture of lime ash filler with variations (5%; 10%; 12.5). 2 RESEARCH METHODS 2.1 Research design The stages of this research are schematically in the form of a flow chart as shown in Figure 2.1 below: A 113

Figure 2.1: Flowchart Research In this study, lime ash was used as a filler of the asphalt used. Asphalt and aggregate properties testing carried out refers to the 2018 Highways Specification Revision 2. The stages used include: 1. Preparation Stage This stage includes the procurement of materials that will be used in the research. The materials used in this study include coarse aggregate, fine aggregate, rock ash filler, lime ash filler, and asphalt. Coarse and fine aggregates, and rock ash filler are from PT. Anugrah Tripa Raya (PT. ATR) bypasses Padang. Lime ash comes from the Padang Panjang area. The tools used are a set of sieves, aggregate inspection test equipment, asphalt inspection test equipment and test equipment for the characteristics of the aggregate and asphalt mixture. 2. Material Test The materials used in this study consisted of coarse aggregate, fine aggregate, filler, asphalt and asphalt with the addition of lime ash first tested according to the test method used. 3. Mix Planning The asphalt content used is from 5% to 7%. The planned lime ash filler content is 0%, 5%, 10%, and 12.5%. 4. Test Object Making At this stage the aggregate is weighed according to the gradation plan. After that, heat the aggregate to a temperature of 150oC, weigh it again before mixing it with asphalt according to the planned levels of 0%, 5%, 10% and 12.5%. After the aggregate and asphalt were mixed, put the mixture into the mold to be pounded as much as 2x75 collisions for marshall. The test objects were made as many as 3 pieces for each asphalt content in the marshall. 5. Testing of Test Items Testing of the test object is volometric testing and marshall testing using the marshall test equipment. Marshall tool is a press tool equipped with a proving ring that is used to support the stability value and a flow meter is used to measure fatigue (flow). The results of the volometric test using the equation obtained the value of Volume of Voids In Solid Asphalt Concrete (VIM), Volume of Aggregate (VMA) and Volume Of Voids Between Aggregates Filled With Asphalt (VFA). After obtaining this volume, the optimum asphalt content is obtained whose function will provide the highest stability of the pavement layer, where other requirements are also met. The equation used is as follows; = 100 − [ ℎ − ] = [ − ] 100 = [ − ℎ ] 100 A 114

Information VMA = volume of aggregate voids in solid asphalt concrete, % of the bulk volume of solid asphalt concrete VIM = volume of voids in solid asphalt concrete, % of bulk volume of solid asphalt concrete VFA = volume of voids between aggregates filled with asphalt, % of VMA Combined Spesific Gravity Bulk 100 % ℎ + % + % Theoretical Spesific Gravity 100 % ℎ + % ℎ ℎ Combined Effective Spesific Gravity 100 % + % + % 3 Results and Discussion 3.1 Aggregate inspection results, Asphalt pen 60/70 and Lime ash The results of testing the properties of aggregate, filler, and asphalt are as shown in Table 3.1, Table 3.2 and Table 3.3. For aggregate testing as a whole, it has met the Technical Specifications of Highways (PUPR, 2018) For testing of asphalt as a whole it has met the Technical Specifications of Bina Marga 2018 Revision 2. Table 3.1: Coarse Aggregate Test Results No Characteristics Results Specification 1. Bulk specific gravity 2,521 2.5 – 2.7 2. SSD density 2,605 2.5 – 2.7 3. apparent density 2,760 2.5 – 2.7 4. AIV (Aggregate Impact Value); (%) 9,202 30% max 5. ACV (Aggregate Crushing Value); (%) 23.209 30% max 6. Los Angeles;(%) 16 40% max 7. Flat Index; (%) 8.55 10% max 8. Index oval; (%) 5.91 10% max 9. Aggregate Weathering; (%) 4.15 10% max From the results of testing the coarse aggregate obtained already meets the standard from the technical specifications of Bina Marga 2018 Revision 2 Division 6 and are listed in the table coarse aggregate requirements. Table 3.2: Fine Aggregate Test Results No Characteristics Results Specification 1. Bulk specific gravity 2.50 2.5 – 2.7 2. SSD density 2,562 2.5 – 2.7 3. apparent density 2.68 2.5 – 2.7 From the results of testing the fine aggregate obtained already meets the standard from the technical specifications of Bina Marga 2018 Revision 2 Division 6 and are listed in the table coarse aggregate requirements. 115

Table 3.3: Filler Test Results No Characteristics Results Specification 1. Specific Gravity of Stone Ash 2,551 2.2 – 2.7 2. Lime Ash Specific Gravity 2,611 2.6 – 2.8 Tests carried out on the filler are specific gravity tests. Function The addition of filler is as a cavity filler in the mixture. Results of filler test get a specific gravity value of . From the value of the test results obtained is 2.551 gr/cm3 then the value of the filler density has been meet the technical specifications of the 2018 Division 6 bina marga, namely 2.2 - 2.7 gr/cm3 . 3.2 Optimum Asphalt content Results Based on the tests carried out, the optimum asphalt content of the mixture using lime ash as a mixture in the filler was obtained. In the 0% variation of lime ash, the optimum asphalt content value was 5.99%; variation of 5% Lime ash obtained optimum asphalt content value of 6.31%; variation of 10% lime ash obtained optimum asphalt content value of 6.57%; and variation of 12.5% Lime ash obtained optimum asphalt content value of 6.60%. In this study, all variations of asphalt mixtures had optimum asphalt content. The comparison of Marshall optimum asphalt content values can be seen in the following graph. Graph 3.1: Comparison of optimum asphalt content Marshall against Lime Ash From Graph 3.1 Marshall's optimal asphalt content has a significant increase at the percentage of lime ash 0%, 5%, and 10%. This is due to the existence of the effect of lime ash that binds asphalt concrete, so that the increase in the variation of lime ash used results in the need for asphalt in the mix increases. 3.3 Asphalt Film Thickness Analysis The comparison of asphalt film thickness for all mixtures in optimum asphalt content and the comparison of aggregate surface area values for each mixture is presented in graph 3.2 below. The asphalt film thickness is strongly influenced by the aggregate gradation, asphalt density and asphalt content in the mixture. Aggregate gradation will affect in determining the value of the aggregate surface area, gradations with more fine fractions will have a larger surface area. At the same aggregate surface area, the higher the asphalt content, the thicker the asphalt film thickness will be compared to the lower asphalt content. High asphalt content is influenced by the addition of lime ash where the more addition of lime ash results in the higher asphalt content. 5.99 6.31 6.57 6.6 5.6 5.7 5.8 5.9 6 6.1 6.2 6.3 6.4 6.5 6.6 6.7 Abu Kapur 0% Abu Kapur 5% Abu Kapur10% Abu Kapur 12,5% Asphalt content (%) 116

Graph 3.2: Asphalt Film Thickness Comparison with Mixed Variations The results of the asphalt film thickness analysis will be very helpful in analyzing the behavior of the mixture in durability testing. The properties of asphalt thickness play a very important role in the accelerated process of asphalt hardening. The results of laboratory tests show that the oxidation process of the asphalt film, at a high room temperature, between 40°C and 60°C to a depth limit of 4 microns (Ricky Kusmawan, 1999). In TRH 8 (National Institute for Transport and Road Research, 1978) it is necessary to calculate the average thickness of the asphalt film layer in the mixture to ensure that this value is not below the required minimum value. For Laston (AC) mixtures, generally the asphalt film thickness requirement is >5 micron (SHELL, 1990). 3.4 Marshall Immersion Test Analysis Immersion test Marshall (Marshall Immersion) is a test to determine the durability of asphalt mixtures. In this test, the mixture was measured for its resistance performance in hot water with a temperature of 60˚C for 30 minutes, 24 hours and 48 hours. This indicates that the mixture is quite susceptible to the influence of water and temperature. This value is expressed by the residual stability value which shows the adhesion behavior between the aggregate grains and the asphalt in the mixture. Based on the results of the research, the asphalt mixture after immersion experienced an increase in stability, where the stability after immersion tends to increase along with the addition of lime ash. Graph 3.3 Comparison of Residual Stability Values for 24 Hours and 48 Hours of Lime Ash immersion 97.52 97.82 99.39 99.66 90.2 95.97 96.01 96.19 90 91 92 93 94 95 96 97 98 99 100 0.0% 2.5% 5.0% 7.5% 10.0% 12.5% 15.0% Stabilitas Sisa (%) Linear ( Marshall Immersion 24 Hour) Linear (Marshall Immersion 48 Hour) 5.93 6.27 6.55 6.58 5.60 5.80 6.00 6.20 6.40 6.60 6.80 Abu Kapur 0% Abu Kapur 5% Abu Kapur 10% Abu Kapur 12,5% Thickness Asphalt Film, µm 117

The durability of the mixture is expressed by the residual stability value. From the results of testing the test object using Marshall Test Equipment with immersion 24 hours and 48 hours. From Graph 4.2, it can be seen that the durability of the mixture tends to increase with the addition of lime percentage, but decreases with the duration of immersion. This increase in durability occurs because lime is generally hydraulic, does not show weathering and can be carried by currents, so that with increasing lime percentage, the durability of the asphalt mixture will increase. It can be seen that the highest residual stability value is found in a mixture of 12.5% lime ash with a value of 99.6% for 24-hour immersion and the lowest value is in a mixture of 0% lime ash with a value of 97.52% for 24-hour immersion. While the residual stability value for 48 hours of immersion tends to decrease from 24 hours of immersion. These results as a whole indicate that the addition of lime ash can increase the performance value of the durability of the asphalt mixture and still meet the minimum requirement of 90%. A mixture of 12.5% lime ash with the highest IKS value compared to other mixtures showed the best level of resistance to the effects of water and high temperatures. The asphalt film factor which is relatively thick compared to other mixtures is estimated to provide the most dominant role in achieving its IKS. With a thick asphalt film, it will ensure the adhesion (adhesiveness) between the asphalt and the aggregate particles is maintained so that it still makes a significant contribution in an effort to minimize the weakening effect caused by water infiltration and high temperatures during the 1x24 hour immersion process. 4 Conclusion 1. Based on the results of tests carried out, the mixture with the addition of lime ash has volumetric characteristics and marshal characteristics in accordance with the 2018 technical specifications revision 2 division 6. 2. Based on the results of testing using the Marshall method carried out at the Civil Engineering Laboratory of the Padang State Polytechnic, the optimum asphalt content values in the AC-WC mixture were as follows: a. Percentage of lime ash 0% with optimum asphalt content value 5.99% b. Percentage of lime ash 5% with optimum asphalt content value of 6.31% c. Percentage of lime ash 10% with optimum asphalt content value of 6.57% d. Percentage of Lime Ash 12.5% with optimum asphalt content value of 6.60% The optimum asphalt content obtained increased in the variation of lime ash 12.5%. 3. From the results of the research, the value of marshal immersion tends to increase with increasing lime ash. The mixture with 12.5% lime ash gave better performance than lime ash (0%, 5% and 10%), this was indicated by the higher residual strength index results, namely for 24 hours immersion of 99.60 and for immersion 48 Hours is 96.19. 5 Bibliography Mahli, M. (2017). The Effect of Using Limestone as a Filler in Asphalt Concrete – Wearing Course (Ac-Wc). Minister of Transportation of the Republic of Indonesia. (2006). Government Regulation Number 34 of 2012 concerning Roads. Vascular Embolotherapy, 107–118. Refi, A. (2019). The Effect of Using Padang Panjang Lime as a Filler on the Characteristics of Asphalt Concrete Mix in AC-BC (Asphalt Concrete-Binder Course) Layer. Rang Engineering Journal, 2 NO. 2(2). Shell, B (1990), The Shell Bitumen Hand Book, Shell Bitumen, UK, 223 – 263. Ricky, K (1999), The Effect of Filler Material and Aggregate Gradation on the Durability of Stone Mastic Asphalt, Master Thesis, Master Program in Highway Systems and Engineering, Bandung Institute of Technology. 118

The Effects of Palm Fibers on Flexural Strength of Concrete Mukhlis1 , Zulfira Mirani2 , Takdir Alamsyah3 , Adinda Shaffira4 And Rifqie Adityo Fawzar5 1 ,2,3,4,5 Civil Engineering Department, Padang State Polytechnic, Kampus St., Limau Manis, Padang, 25164 INDONESIA *Corresponding Author: [email protected] Abstract: Concrete is one of the most commonly used materials in construction. However, concrete itself is a material with low flexural strength. Flexural strength is the amount of tensile load concrete can bear before failing, which is an important characteristic of concrete. Flexural strength is required in rigid pavement design. One of the ways to improve concrete strength is the usage of fiberreinforced concrete. Fiber-reinforced concrete utilizes various types of fiber, one of them being natural fibers. Palm fiber is one of the commonly used unprocessed natural fibers, as well as an easy material to get. This experiment was done to find out the effect of palm fibers on flexural strength of concrete to determine whether palm fibers can be used in concrete or not. The research was done with concrete samples sized 15 cm x 15cm x 60cm. The variations of the concrete mixture were the addition of 0%, 1.5%, 2.5%, and 3% palm fibers, alongside the variations of fine aggregates of Grading Zone II and Grading Zone IV. Flexural strength test was conducted at concrete age of 28 days, with 2 samples per variation. The test conducted referred to SNI 4431:2011 method of testing concrete flexural strength. The result showed that the highest flexural strength achieved in a mixture using Grading Zone II fine aggregate is at 0% palm fiber with a flexural strength of 3.59 MPa. The highest flexural strength achieved in a mixture using Grading Zone IV aggregate happened when 1.5% palm fiber was added into the mixture, which caused a flexural strength of 2.86 MPa. Keywords: Fiber-Reinforced Concrete, Palm Fiber, Flexural Strength 1. INTRODUCTION The usage of concrete as rigid pavement is one of the many utilizations of concrete commonly used. The development of technology and infrastructure requires the development of concrete technology to improve concrete strength. One of the many ways to improve concrete strength is the usage of fiber-reinforced concrete. Fiber-reinforced concrete is a type of concrete that utilizes various types of fiber, such as steel fibers, glass fibers, synthetic fibers, and natural fibers. Fibers are used to prevent cracks on concrete, thus making concrete more ductile and increasing the flexural strength of concrete (Haq dan Andayani, 2017). This makes concrete more durable against tensile force caused by weather, climate, and temperature. Concrete is one of the materials that are widely used in various construction nowadays, thus improving concrete properties and performance is in high demand to keep up with construction needs. Several studies regarding fiber-reinforced concrete have been done in the past. Winarto (2017) studied the effect of palm fibers in concrete mixture to improve the ability of concrete to withstand compressive loads with the proportion of palm fibers of 0%, 2.5%, and 5%. The study resulted in finding the optimum proportion of palm fiber at 2.5%, with a compressive strength of 226 kg/cm2 . The addition of palm fiber in concrete mixture also causes the concrete to be lighter in weight. 1.1 Concrete Concrete is a mixture of Portland cement or other hydraulic cement, fine aggregate, coarse aggregate, and water, with or without additives, to form a solid mass. Normal concrete has a unit weight of 2200 – 2500 kg/m3 (SNI 03-2834-2000). 119

1.2 Fiber-Reinforced Concrete Fiber-reinforced concrete is a type of concrete that is made from hydraulic cement containing fine aggregate, coarse aggregate, and discontinuous discrete of fibers (American Concrete Institute, 2002). The addition of fiber is to increase the flexural strength of concrete and prevents cracks. The addition of fiber in fiber-reinforced concrete can decrease the concrete’s compressive strength but increases flexural strength (Wora, M., and Ndale 2018). Types of fibers commonly used in fiber-reinforced concrete are steel fiber, glass fiber, synthetic fiber, and natural fibers. This study will utilize unprocessed natural fiber, which is palm fiber. 1.3 Palm Fiber Palm fiber is a natural fiber produced by the palm tree (Arenga pinnata). Palm fiber is a resource that can be found abundantly throughout Indonesia, making it an easily accessible resource and is a great alternative for unprocessed natural fiber in fiber-reinforced concrete. Palm fiber can also last for decades and is also durable against salt and seawater. Palm fiber has the physical appearance of black threads, with its edge tinted red, is soft, rigid, and does not break easily when pulled. Palm fiber consists of several chemical elements, such as 51.54% cellulose, 15.88% hemicellulose, 43.09% lignin, 8.9% water, and 2.54% ash (Harista and Bastian 2022). 1.4 Concrete Mix Design Concrete mix design is a process of calculation to find the right composition of cement, coarse aggregate, fine aggregate, water, and additives in concrete. Several methods used in concrete mix design are Fineness Modulus Method, American Concrete Institute (ACI) Method, Department of Environment Method, and Indonesian National Standard/Standar Nasional Indonesia (SNI) method. In this study, the method used for concrete mix design is Standar Nasional Indonesia (SNI) 03-2834-2000. This method is used for normal concrete mix design. 1.5 Concrete Flexural Strength According to SNI 4431:2011, concrete flexural strength is the ability of a concrete beam placed on two supports to withstand forces in a direction perpendicular to the axis of the test object and is expressed in MPa. According to SNI 8457:2017, the minimum flexural strength for rigid pavement for low-volume roads is 3.5 MPa for local roads, 3.8 MPa for collector roads, and 4.1 MPa for special roads. In this study, concrete flexural strength is tested according to SNI 4431:2011. For testing in which fracture field happens in 1/3 of the middle section, equation (1) is used. = . .ℎ2 (1) For testing in which the fracture field happens outside 1/3 of the middle section, equation (2) is used. = . .ℎ2 (2) In which σl is flexural strength (MPa). P is the highest force read in the testing machine (kN). L is the distance between two placement lines (mm). b is horizontal-direction fracture cross-section (mm). h is vertical-direction fracture cross-section (mm). a is the average distance between the fracture cross-section and the closest support (mm). The fractures referred to above are illustrated in Fig.1, in which Fig.1(a) illustrates the fracture within 1/3 of the middle section while Fig.1(b) illustrates the fracture happening outside of the 1/3 middle section. This fracture can be observed visually during the testing. 120

(a) (b) Figure 1: (a) Fracture in 1/3 Area of the Middle Section and (b) Fracture Outside of 1/3 Area of the Middle Section and Fracture Line within < 5% of Beam 1.6 Literature Review Pertiwi and Sabariman (2017) studied the effects of palm fiber on concrete flexural strength using the variations of 0%, 1%, and 3% of cement volume. The study resulted on increase on flexural strength of 147.33% at variation of 1% and increase of 54.53% at variation of 3%. Perdana et al. (2015) studied the effects of palm fiber in concrete tensile strength. The variations used are 2.5%, 5%, 7.5%, and 10% of palm fiber. The study resulted in increase of concrete tensile strength, with the highest tensile strength achieved at variation of 10%, which is 2,667 MPa. Wora and Ndale (2018) studied the effects of palm fiber on concrete tensile strength using the variations of fiber length (1 cm, 1.5 cm, 2 cm, 2.5 cm, and 3 cm) and compositions (0%, 1%, 2%, and 3%). The study resulted decrease of compressive strength and increase of tensile strength at each variation. The highest tensile strength achieved was 3,35 MPa, with the variation of 3% of 3 cm palm fibers. Munandar et al. (2013) studied the tensile strength of palm fiber with the variation of palm fiber diameter (0.25 – 0.35 mm and 0.46 – 0.55 mm). The study found that palm fiber with smaller diameter has higher tensile strength. 2. RESEARCH METHOD 2.1 Research Planning Concrete mix design is based on Standard Nasional Indonesia (SNI) 03-2834-2000. Concrete flexural strength test refers to Standard Nasional Indonesia (SNI) 4431:2011. The procedures of the test can be seen in the flowchart in Fig.2. There are four variations of palm fiber addition, which are 0%, 1.5%, 2.5%, and 3% of cement weight. Palm fibers are cut into ± 5 cm and added homogeneously into the mixture during the mixing phase. Towards each proportion of palm fiber, there are two variations of fine aggregate, which are Grading Zone II and Grading Zone IV. The samples are then molded using a 15 cm × 15 cm × 60 cm mold and cured. The number of samples can be seen in Table 1. 2.2 Research Implementation The study is done at the Laboratory of Material Testing, Civil Engineering Department, Padang State Polytechnic and the Laboratory of Construction Material, Ministry of Public Works and Public Housing, West Sumatera. 121

Figure 2: Research Procedure Flowchart Table 1: Variation and Numbers of Samples Variation of concrete mixture Concrete age 28 hari Fine aggregate type Fiber percentage Flexural Strength Grading Zone II 0% 2 1.5% 2 2.5% 2 3% 2 Grading zone IV 0% 2 1.5% 2 2.5% 2 3% 2 TOTAL 16 3. RESULT AND ANALYSIS 3.1 Testing of Fresh Concrete During the mixing of concrete, slump tests and unit weight tests are done. The result of slump test can be seen in Table 2 and Table 3. Table 2: Result of Slump Test on Concrete Mixture with Grading Zone IV Fine Aggregate Fiber percentage (%) Average slump (cm) Slump required (cm) Water addition (kg) 0% 6,10 5.0 – 7.5 0,81 1.5% 6,28 5.0 – 7.5 2,62 2.5% 9,38 5.0 – 7.5 2,43 3% 8,25 5.0 – 7.5 1,86 Table 3: Result of Slump Test on Concrete Mixture with Grading Zone II Fine Aggregate Fiber percentage (%) Average slump (cm) Slump required (cm) Water addition (kg) 0% 6,10 5.0 – 7.5 0,53 1.5% 6,28 5.0 – 7.5 2,99 2.5% 5,13 5.0 – 7.5 3,18 3% 8,25 5.0 – 7.5 3,49 122

Slump is defined as the consistency of fresh concrete which affects permeability, workability, and the work process of concrete. Several things that affect slump are the size of aggregate, number of water, and the effect of water on cement. As stated in Table 2 and Table 3, the range of slump allowed in this testing is 5 – 7,5 cm. To reach the required range of slump, the addition of water is needed. It is due to the absorption of water on aggregate is high, and the water content in aggregate might be different than previously tested. Aside from that, palm fiber absorbs water, causing the need for more water to reach the correct consistency. As can be seen in Table 3, water addition in concrete mixture with Grading Zone II fine aggregate increases proportionally with the increase of fiber percentage. This happens due to the absorption capability of palm fiber. The more palm fiber added into the mixture, the more water absorbed by the palm fiber, causing the need for more water to be added to reach the desired consistency. However, according to Table 2, on concrete mixture with Grading Zone IV fine aggregate, the highest water addition happens at the percentage of palm fiber of 1.5%, while the addition of water at 2.5% palm fiber and 3% palm fiber are met with decrease of water addition. This can happen due to differences in water content in aggregate during the mixing. This phenomenon can happen when materials aren’t stored properly, causing differences in water content. However, compared to mixture with 0% palm fiber, increase of water addition still occurs. This is happening because palm fiber absorbs the water when mixed. In addition, the addition of more water than needed causes the mixture to reach a collapse consistency, exceeding the maximum range of slump allowed. Concrete unit weight is affected by materials unit weight and density of mixture. Aside from the fine aggregate, materials used in both mixtures have the same quality. Thus, we can conclude that the unit weight is affected by mixture density. The higher the mixture density, the higher the concrete unit weight. Concrete unit weight testing result can be seen in Fig.3. (a) (b) Figure 3: Concrete Weight with (a) Grading Zone II and (b) Grading Zone IV Fine Aggregate In concrete mixture with Grading Zone II fine aggregate, there is a proportional increase of unit weight from 0% palm fiber variation to 3% palm fiber variation. However, in mixture with Grading Zone IV fine aggregate, there is a decrease in unit weight from 0% to 3%. This can be caused due to distribution of fine aggregates and palm fibers. In concrete with Grading Zone II fine aggregate, fibers fill the gaps between coarse and fine aggregate well, making the mixture more dense and heavier unit weight. However, in concrete with Grading Zone IV fine aggregate, palm fiber does not only fill the gap in the mixture, but also takes over some of fine aggregate away, making the concrete lighter. 3.2 Testing of Concrete Flexural Strength Testing of concrete flexural strength is done at concrete age of 28 days. Flexural strength is calculated using Equation (2), in which the cracks happen in the 1/3 of the middle area of samples. The result of concrete flexural strength testing of concrete mixture with Grading Zone IV fine aggregate can be seen in Table 4. According to Table 4, the maximum flexural strength achieved for concrete with Grading Zone IV fine aggregate happens at the variation of 1.5% palm fiber. The flexural strength achieved is 2.86 MPa, or 105% of the flexural strength of normal concrete (0% palm fiber). However, palm fiber does not give a positive influence for concrete mixture using Grading Zone II fine aggregate, where the maximum flexural strength achieved is at 0% palm fiber, which is 3.59 MPa. 123

Table 4: Flexural Strength of Concrete Using Grading Zone IV Fine Aggregate Fiber percentage (%) Flexural strength (MPa) Average flexural strength (MPa) 0 2,59 2,71 2,84 1,5 2,69 2,86 3,03 2,5 2,23 2,20 2,17 3 2,18 2,11 2,04 The result of concrete flexural strength testing of concrete mixture with Grading Zone II fine aggregate can be seen in Table 5. Table 5: Flexural Strength of Concrete Using Grading Zone II Fine Aggregate Fiber percentage (%) Flexural strength (MPa) Average flexural strength (MPa) 0 3,72 3,59 3,47 1,5 3,06 3,37 3,68 2,5 3,23 3,15 3,08 3 2,76 2,58 2,39 In Table 5, we can see that the flexural strength decreases for concrete with Grading Zone II fine aggregate, with the highest flexural strength happening at the 0% palm fiber variation. This shows that there is no positive effect of palm fiber in the mixture. This might happen due to the slippery nature of palm fiber surface, causing the cement paste to not bind the palm fiber correctly. This can be caused due to palm fiber being mixed directly during the mixing process, causing the distribution of fiber in the mixture to not be as evenly and controlled as possible, which affects the benefit of the fiber in concrete strength. 4. CONCLUSION From the study, we can conclude that the maximum flexural strength achieved by concrete with Grading Zone IV fine aggregate is with 1.5% palm fiber, with the flexural strength of 2.86 MPa. However, the usage of palm fiber does not affect concrete with Grading Zone II fine aggregate positively, with the maximum flexural strength achieved being at 0% palm fiber, which is 3.59 MPa. 124

5. REFERENCES Aly, M. A. 2004. Teknologi Perkerasan Jalan Beton Semen. Jakarta: Yayasan Pengembangan Teknologi dan Manajemen. American Concrete Institute. 2002. ACI 544.1R-96 Report on Fiber Reinforced Concrete. Badan Standarisasi Nasional. 1989. SK SNI S-03-1989-F. Badan Standarisasi Nasional. 2000. SNI 03-2834-2000 Tata Cara Pembuatan Rencana Campuran Beton Normal. Badan Standarisasi Nasional. 2002. SNI 03-2847-2002 Tata Cara Perhitungan Struktur Beton untuk Bangunan Gedung. Departemen Pekerjaan Umum. 2005. Pd T-07-2005-B Pelaksanaan Pekerjaan Beton untuk Jalan dan Jembatan. In Departemen Pekerjaan Umum Haq, H. A., & Andayani, R. 2017. Pengaruh Penambahan Serat Kawat Bendrat Dan Serat Ijuk Pada Beton K225 Terhadap Kuat Geser. Jurnal Desain Konstruksi, 16(1): 76–82. Munandar, I., Savetlana, S., & Sugiyanto. 2013. Kekuatan Tarik Serat Ijuk (Arenga Pinnata Merr). Jurnal FEMA, 1(3): 52–58. Perdana, A. O., Wahyuni, A. S., & Elhusna. 2015. Pengaruh Penambahan Serat Ijuk Terhadap Kuat Tarik Belah Beton Dengan Faktor Air Semen 0, 5. Inersia: Jurnal Teknik Sipil, 7(2): 7–12. Pertiwi, D. R. R., & Sabariman, B. 2017. Pengaruh Penambahan Serat Ijuk Terhadap Kuat Lentur Balok Beton Bertulang. Rekayasa Teknik Sipil, 1(1): 247–255. Winarto, S. 2017. Pemanfaatan Serat Ijuk Sebagai Material Campuran Dalam Beton Untuk Meningkatkan Kemampuan Beton Menahan Beban Tekan. UkaRsT, 1(1): 1–10. Wora, M., & Ndale, F. X. 2018. Pengaruh Penambahan Serat Ijuk Dapat Meningkatkan Kuat Tarik pada Beton Mutu Normal. Jurnal IPTEK, 22(2): 51–58. 125

Gamification in Teaching Material Science & Engineering at Politeknik Banting Selangor During COVID-19 Hanis Rasyidah Abdullah1 , Nur Raihana Sukri2 And Intan Liyana Ramli3 1,2,3 Politeknik Banting Selangor, Banting, 42700, MALAYSIA *Corresponding Author: [email protected] Abstract: One of the most important courses in the Politeknik curriculum is Material Science and Engineering. The majority of students, however, perceive the course to be bland and uninteresting. This was seen in the course's results for the semester of June 2019, where 79.9% of students achieved grade C and above. This is lower than the Politeknik Banting Selangor’s key performance indicator in course outcome review report (CORR), 90% of students targeted achieving grade C and above. Is it possible to use gamification to make the course more exciting and engaging? This study investigates how Diploma of Mechanical Engineering students performed in the final examination of Material Science and Engineering when lecturers used gamification as a creative asynchronous teaching approach during COVID-19. The sample for this case study was constituted of 174 respondents from semester two of the Diploma in Mechanical Engineering, which includes all participants who took the course of Material Science and Engineering during short semester 2021 session. Their final grade received was analyzed and compared to the final grade results of 189 Diploma in Mechanical Engineering students for Material Science and Engineering subject for the June 2019 session, when the gamification is not implemented in teaching and learning. Remarkably, 99.4% of students scored grade C and above on for short semester 2021 when gamification was used. This astonishing outcome demonstrates that gamification is a significant tool for making the course more interesting and it could be used as an asynchronous teaching technique in order to improve students’ performance. In the near future it could be investigated how lecturers and students perceive the use of gamification. Keywords: Gamification, Covid-19, asynchronous teaching, material science. 1. INTRODUCTION The coronavirus Covid-19 has proven to be a deadly disease transmitted through acute respiratory syndrome and some common cold (Ciotti et al., 2019). It’s called a pandemic because it has spread quickly and caused a lot of damage (Shah et al., 2020). After the first Movement Control Order (MCO) enacted in response to the epidemic, all states in Malaysia were put into a state of lockdown. Lecturers and higher educational institutions around the world have had to quickly adapt their teaching approaches due to the pandemic. In an effort to stop the spread of the virus, Politeknik Banting Selangor agreed to the recommendations of health professionals and redesigned all teaching practices, including lectures and laboratory activities. Due to the lack of face-to-face contact, significant effort has been put into developing innovative teaching methods in the hopes that these methods will simultaneously increase students' ability to learn while increasing their passion and dedication to their studies. Instructional strategies can be divided into synchronous and asynchronous activities. During synchronous teaching, students and lecturers were able to communicate in real time through video and audio conferences. Meanwhile, students and lecturers don't have to communicate in real time in asynchronous teaching activity. Studies have shown that students' ability to process and understand information and their ability to manage their time both are improved by asynchronous learning (Higgins et al., 2022). It has become increasingly important to produce teaching materials that are consistent with social distance as the Covid-19 epidemic grows. Technology stimulates the development and sharing of new knowledge, but lecturers must find new ways to engage and enthuse their students in order to reap the benefits. Students' 126

attention spans will improve if lecturers put in more time and effort to prepare for online courses, create new lessons, and improve existing ones. In recent years, educators have increasingly turned to gamification as a tool for engaging and motivating their students to study (Nieto-Escamez & Roldán-Tapia, 2021; Rincon-Flores et al., 2022; Suppan et al., 2020). 1.1 Problem Statement Material Science and engineering is one of the most significant courses in the Politeknik curriculum. Most students, however, find the course to be dry and uninteresting. This was seen in the course outcome review report for semester June 2019 where only 59% of students are able to explain the fundamental of material science including identification of various types of materials, mechanical behavior, metal production processes and various principles of material testing, and overall, 79.9% of students score grade C and above. This is far from the targeted goal, 90% of students achieving grade C and above. Is it possible to make the course more interesting and engaging by using gamification especially during Covid-19? Is gamification effective to reinforce the key concept to the students? The purpose of this case study was to investigate the performance of Diploma of Mechanical Engineering students in the Material Science and Engineering subject when their lecturer employed gamification as a creative asynchronous teaching approach during the Covid-19. The researchers were especially interested in how well the students performed because most instructors were concerned about the impact of technology on students' education in light of the current pandemics and Malaysia's rapid rise of online learning. 2. LITERATURE REVIEW A literature review was conducted as part of the initial phase of the investigation. The primary focus was on online teaching and gamification. 2.1 Online Teaching and Learning During Covid-19 Pandemic The pandemic caused by Covid-19 has forced all educational institutions to shut down, while educators and Higher Educational Institutes (HEIs) have been urged to change their teaching methods immediately. As a direct consequence of this, the majority of classes is delivered remotely to ensure social distancing (Johnson et al., 2020). Report written by Marinoni et al. (2020) shows that 85% of HEIs in Europe, 60% HEIs in Asia & Pacific, 72% HEIs in Americas and 29% HEIs in Africa replaced the conversional teaching into remote teaching and learning. Several academicians have distinguished between online and remote teaching. The term "online teaching" refers to courses that are offered using various websites, whereas "remote teaching" refers to a temporary teaching approach used in response to a specific situation such as Covid-19 (Higgins et al., 2022). However, not all HEIs are prepared for this emergency shift, particularly in Africa, where 24% of their HEIs are cancelled teaching (Marinoni et al., 2020). Meanwhile, the Malaysian government is instructing all HEIs to switch from campus to remote teaching (Ma et al., 2022; Sia & Adamu, 2020). The continued advancement of digital technology has enabled students to adhere to social distancing when learning online. The most popular platforms used by lecturers when teaching in real time are Google Meet, Webex, Microsoft Teams and Zoom (Cavus & Sekyere-Asiedu, 2021; Dash et al., 2021). In order to tackle the issue of students with limited internet access, some lecturers opted to record their lesson and broadcast it to a YouTube channel, so that students could watch it at their own convenience (Roza, 2021; Yaacob & Saad, 2020). Politeknik Banting Selangor encourages lecturers and students to make use the Microsoft Teams by providing the institutional account for free. During the lockdown period, certain institutions are deploying the virtual and remote laboratories (Flynn et al., 2021; Müssig et al., 2020; Radhamani et al., 2021) using simulators or augmented reality techniques, as recommended by Andujar et al. (2010) and Odeh et al. (2015) earlier. However, not all institutions have the necessary resources to develop simulator and augmented reality-based laboratories. Therefore, they use alternative methods such as guided home experiments. Students are tasked with creating the experiment, obtaining the appropriate equipment, assembling the components, carrying out the experiment and uploading their experiment video (Endrasari et al., 2022). This method also widely used in Politeknik Banting Selangor for laboratories work. Gamage, Wijesuriya, et al. (2020) reviews the various methods that utilized by institutions to deliver teaching and laboratory activities during Covid-19. One of the greatest challenges in online teaching and learning is student assessment. Many institutions have resorted to alternative forms of student assessment during the COVID-19 pandemic. Activities for assessing 127

learning, such as quizzes and examinations, have been created to be tracked and monitored online. Rahim (2020) presented nine guidelines as a means of assisting institutions in designing online assessment. Students are subject to virtual invigilation during online exams to prevent them from engaging in unethical activity such as cheating (Gamage, Silva, et al., 2020; Tuah & Naing, 2021). Online teaching and learning has been tough and unpleasant for everyone involved, especially the lecturers and students (Tanveer et al., 2020). It necessitates lecturers to work hard to find strategies to improve students' motivation and engagement. Lecturers who wish to be better equipped to deal with global threats like the Covid-19 pandemic should enroll in online learning training (Tuah & Naing, 2021). The COVID-19 pandemic has brought to light both the strengths and flaws of our educational system and made it clear that using digital tools to enhance and support teaching was a wise decision (Higgins et al., 2022). 2.2 Gamification as A Tool to Enhance Students’ Learning Performance Developing educational technologies that are compatible with social distancing is crucial at a time marked by Covid-19. This is because millions of students are being quarantined in an effort to slow the spread of the epidemic. In recent years, educators have become increasingly interested in exploring the possibilities of gamification to enhance student learning (López Carrillo et al., 2019; Nieto-Escamez & Roldán-Tapia, 2021; Rincon-Flores & Santos-Guevara, 2021). Gamification is the integration of gameplay principles into non-game settings with the intention of fostering learning. The use of gamification in educational settings as a method to increase students' motivation and improve social interaction has become increasingly common over the past decade (Nieto-Escamez & Roldán-Tapia, 2021; Wiggins, 2016). The ability of gamification to improve learning outcomes has been demonstrated through its application in numerous educational environments and at different levels of education. In general, student feedback indicated that gamification was creative, interesting, and an effective method for delivering curricular material; in addition, it was regarded as a pleasurable activity to participate in (NietoEscamez & Roldán-Tapia, 2021). Gamification has been shown to be effective in reinforcing key concepts and subjects learnt in class (Oe et al., 2020). Politeknik Banting Selangor held several online trainings for lecturers to set up gamification for teaching and learning. However, no research has been conducted on the impact of gamification in Politeknik Banting Selangor so far. 3. METHODOLOGY A non-experimental research design was adopted in this study, as shown in Figure 1. Firstly, lecturers create online gamification as learning materials for each topic that students can use for revision during short semester 2021 session. The URL was given to the students through the Microsoft Teams posts section for each topic. Students' participation and performance in each game session were monitored, and the topic that received the lowest score is further explained during synchronous remote teaching. The sample for this study was constituted of 174 respondents from semester two of the Diploma in Mechanical Engineering, which includes all participants who took the course of Material Science and Engineering during short semester 2021 session, when the gamification is implemented. Their final grade received was compared to the final grade results of 189 Diploma in Mechanical Engineering students for Material Science and Engineering subject for the June 2019 session, when the gamification is not yet implemented in teaching and learning. However, same lecturers were teaching for both sessions. The histograms chart is used to show the comparison of final grade. All course assessments in Politeknik Banting Selangor are designed to meet the course learning outcome (CLO) and programme learning outcome (PLO). A course outcome review report (CORR) is generated at the end of the semester. For this case study, the course learning outcome 1 (CLO1); “apply the fundamental of material science to identify the materials, properties, behavior, process and treatment”; and programme learning outcome 1 (PLO1); “apply the knowledge of mathematics, science and engineering fundamentals to well-defined mechanical engineering procedures and practice”; were examined too. The CLO1 and PLO1 are most related to the purpose of gamification, which is to reinforce the key concept to the students. 128

Figure 1: Methodology of the study 4. DISCUSSION The final grade of 174 Diploma in Mechanical Engineering students during the short semester of 2021 are presented in Table 1. The highest frequency is grade A, where 36.8% of students scored A. Meanwhile only 1 student obtained a grade of C and C-. This finding is absolutely encouraging, the gamification method should be implemented extensively, not just during the lockdown period caused by Covid-19. Table 1: Results for Short Semester 2021 Session Grade Percentage A+ 11.5 A 36.8 A- 24.1 B+ 11.5 B 10.9 B- 4 C 0.6 C- 0.6 The histograms in Figure 2 compares student performance between the June 2019 session and the short semester 2021 session. When compared to the June 2019 session, no students failed this course during the short semester 2021 session. The 36.8% of students earned an A grade during the short semester 2021 session, which represents a significant leap forward compared to the June 2019 session, where the highest frequency is 21.2% for grade C+. It has been convincingly demonstrated that student performance improves when gamification is employed as a learning tool. Lecturer provide the URL of online gamification as learning materials for each topic Students do asynchronise revision for the course using gamification Students take all the assessments for the course (quizzez, tests, final examination) Lecturer generate the course outcome review report Lecturer analyze the grade, CLO1 and PLO1 129

Figure 2: Comparison of Students Performance Before and After Gamification Table 2 below shows the CORR summary of group attainment for CLO1 and PLO1. The 19% increment for CLO1 and 15% increment for PLO1 has been recorded when gamification is implemented during short semester 2021 session. As a conclusion, gamification is an effective tool for helping students better grasp the key concept being taught. Table 2: CORR for CLO1 and PLO1 group attainment Item Jun 2019 SS 2021 CLO1: Apply the fundamental of material science to identify the materials, properties, behavior, process, and treatment 59% 78% PLO1: Apply the knowledge of mathematics, science and engineering fundamentals to well-defined mechanical engineering procedures and practice 63% 78% 5. SUMMARY As was mentioned, gamification has attracted the attention of researchers as a means to support students' learning. The purpose of this study was to determine students’ performance in final exam when gamification is employed in teaching Material Science and Engineering during the Covid-19 pandemic. The findings demonstrated that student performance improves when gamification is employed as a learning tool. Gamification empowers students to direct their learning and increases their enthusiasm to investigate the topics they were discovering about through games. This method should be implemented extensively, not just during the lockdown period caused by Covid-19. A+ A A- B+ B B- C+ C C- D+ D E E- F Jun-19 0 0.5 4.8 6.3 14.3 15.9 21.2 16.9 5.3 6.3 3.7 3.7 0 1.1 Short Sem 2021 11.5 36.8 24.1 11.5 10.9 4 0 0.6 0.6 0 0 0 0 0 0 5 10 15 20 25 30 35 40 Percentage 130

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Oe, H., Takemoto, T., & Ridwan, M. 2020. Is gamification a magic tool?: Illusion, remedy, and future opportunities in enhancing learning outcomes during and beyond the COVID-19. Budapest International Research and Critics in Linguistics and Education (BirLE) Journal, 3(3), 1401-1414. Radhamani, R., Kumar, D., Nizar, N., Achuthan, K., Nair, B., & Diwakar, S. 2021. What virtual laboratory usage tells us about laboratory skill education pre-and post-COVID-19: Focus on usage, behavior, intention and adoption. Education and information technologies, 26(6), 7477-7495. Rahim, A. F. A. 2020. Guidelines for online assessment in emergency remote teaching during the COVID-19 pandemic. Education in Medicine Journal, 12(3). Rincon-Flores, E. G., & Santos-Guevara, B. N. 2021. Gamification during Covid-19: Promoting active learning and motivation in higher education. Australasian Journal of Educational Technology, 37(5), 43-60. Roza, V. 2021. Incorporating both Zoom and YouTube in Micro Teaching Class during the Covid-19 Pandemic: An Effectiveness Investigation. Journal of Physics: Conference Series. Shah, A. U. M., Safri, S. N. A., Thevadas, R., Noordin, N. K., Abd Rahman, A., Sekawi, Z., . . . Sultan, M. T. H. 2020. COVID-19 outbreak in Malaysia: Actions taken by the Malaysian government. International Journal of Infectious Diseases, 97, 108-116. Sia, J. K.-M., & Adamu, A. A. 2020. Facing the unknown: pandemic and higher education in Malaysia. Asian Education and Development Studies. Tanveer, M., Bhaumik, A., Hassan, S., & Haq, I. U. 2020. Covid-19 pandemic, outbreak educational sector and students online learning in Saudi Arabia. Journal of Entrepreneurship Education, 23(3), 1-14. Tuah, N. A. A., & Naing, L. 2021. Is online assessment in higher education institutions during COVID-19 pandemic reliable? Siriraj Medical Journal, 73(1), 61-68. Wiggins, B. E. 2016. An overview and study on the use of games, simulations, and gamification in higher education. International Journal of Game-Based Learning (IJGBL), 6(1), 18-29. Yaacob, Z., & Saad, N. H. M. 2020. Acceptance of YouTube as a learning platform during the Covid-19 pandemic: the moderating effect of subscription status. Tem Journal, 9(4), 1732. 132

Occupational Stress: Analysis of Polytechnic Academicians During COVID-19 Pandemic Using Modified HSE UK Management Standards Segar Rajamanickam1 , Mohamad Amirul Azwan Mohamed Yusof 2 And Khairol Adha Ahmad3 1 Principal Lecturer Department of Electrical Engineering, Polytechnic Seberang Perai, Penang, MALAYSIA. 2 HSE Executive, Shaziman Transport Sdn Bhd, Klang Valley Distribution Terminal, MALAYSIA. 3 Senior Lecturer Department of Electrical Engineering, Polytechnic Mukah Sarawak, Sarawak, MALAYSIA. *Corresponding author: [email protected] Abstract: Occupational stress research has made many advances throughout the past two decades, yet there is much to learn about them. One such scenario that necessitates the need for further research on occupational stress is whenever an outlier evolves the traditional view of the work environment in the context of occupational stress such as during the Covid-19 pandemic of 2020. This research employed a quantitative approach to ascertain the instances and the stressors regarding occupational stress. Data were collected from a convenience sample of 52 Polytechnic Academicians from who completed a questionnaire recording a rating of psychosocial factors that are the source of their stressors. Descriptive analysis is then applied on the questionnaire’s data, which uses a single-item measure of Likert Scale to identify the main themes. The analysis yielded a prevalence for occupational stress of 55.8% with the most common frame of reference being high job demands. Imbalances to the work-life interface emerged as the secondary dominant theme as boundaries of work-life interface blur. More than half of the respondents reported stress symptoms with only ten respondents reporting no adverse health effects suffered. The findings from this research may help illuminate on occupational stress exacerbated by work-life interface imbalances. And as more research is being done on this subject, it may help formulate specific interventions towards occupational stress during a pandemic. Keywords: Occupational Stress, Covid-19 Pandemic, HSE Management Standards, Work-Life Interface, Job-Demand Control Model 1. INTRODUCTION Occupational Stress is the harmful physical and emotional responses that occur when the job requirements do not match the capabilities, resources, or needs of the worker (De Silva, Samanmali, & De Silva, 2017). The relationship between work and health is an essential concern for employers as the impact of work on health is vital in promoting health and preventing diseases. It has been attributed that the etiology of Occupational Stress is psychosomatic diseases and poor mental health. Traditionally, Occupational Stress can be found largely on employees working in a traditional setting, videlicet, employees working normally at the workplace. These employees normally have a balanced work-life interface, and Occupational Stress will only occur when there is a disruption on the work-life interface or other psychosocial-environmental conditions. Little studies, however, has been done for cases of Occupational Stress as a result of massive life-altering conditions such as during a pandemic. On 31 December 2019, the world is alerted to the emergence of Coronavirus infections which at that time are only endemic in China with the first case being reported around three months before. Since then, due to globalization, the contagion started to spread all over the world. This prompted the World Health Organization (WHO) to declare Coronavirus infections a Public Health Emergency of International Concern (PHEIC) on 30 January 2020, a month after the outbreak first reported by China to WHO. The infections are then named Covid-19. Malaysia is among the country profoundly affected by this pandemic. With a total case as of 27 March, 2020 at 2161 active case and 26 cases of death, the effects of Coronavirus on Malaysian are far-reaching, from the negative health impacts of the infections to fear and panic brought 133

upon it as well. Apart from that, Malaysian Government in an effort to curb further spread of Coronavirus implemented Movement Control Order (MCO) starting from 28 March 2020 until 14 April 2020 which limited movement of Malaysian as well as shutting down non-essential services. This prompted many employers directing their employees to work from home or telecommuting. As employees work during this pandemic, whether it is from home or at the frontline fighting as a collective against Coronavirus, there is a need to ascertain their psychological state, especially in these exacting times. As Prasad, Vaidya and Mangipudi (2020) iterated in their analysis regarding Occupational Stress & remote working on psychological well-being of employees, there is a statistical significance of Occupational Stress on psychological well-being of employees by means of correlation coefficient, R=0.447 (Prasad, Vaidya, & Mangipudi, 2020). This shows that there is a moderate level of association of Occupational Stress on psychological well-being. Wong, Yee and Chorh (2020) in their article regarding critical issues that require concerted, coordinated attention and action on Covid-19 accentuates the need for stress management especially among health workers (Wong, Yee, & Chorh, 2020). During the early phase of SARS outbreak in 2003, Xiang et al.,(2020) stated that a range of psychiatric morbidities such as persistent depression, anxiety, panic attacks, psychomotor excitement, psychotic symptoms, delirium and even suicidality were reported (Xiang, et al., 2020) All of these symptoms are a classic clinical presentation of Occupational Stress, and if there are no measures taken to assuage stressors associated with Occupational Stress, the symptoms progress might deteriorate until the affected person might not be able to function normally and in the worstcase scenario, chooses death as an easy way out. 2. PROBLEM STATEMENT The advent of Coronavirus pandemic in 2020 has caused a multitude of problems, whether it is health-related or economic related. One area of increasing concern is the mental health effects of it, especially in terms of Occupational Stress. Addressing this problem will have practical benefits to workers experiencing occupational stress during the pandemic and furthermore contribute to understanding the stressors and effects of a pandemic on the workforce. It should be of note that an employer's duty of care should be augmented beyond the duty physical injury to mental health damage and that the employer shall provide the persons under their care with a well thought out safe system of work that not only compasses of management of traditional hazards (physical, biological, chemical) in nature but also of the psychosocial and psychiatric in nature. Traditionally, a safe system of work focuses heavily on the effect of traditional hazard on the workers' well-being but not on the effect of psychosocial hazards itself. Indeed, Fiksenbaum (2014) articulated that a safe system of work that encompasses from development of organizational policies to formal safe system of work practices helps in supporting employees managing psychosocial hazards (Fiksenbaum, 2014). This view is supported by Mansour & Tremblay (2018) in their research regarding implications of safe system of work on impacts of psychosocial hazards where they observed that whenever organizations put in place an effective safe system of work in managing psychosocial hazards, employee’s wellbeing are taken care of positively and this translate to increase in productivity & performance in said organizations (Mansour & Tremblay, 2018). Conversely, with no effective safe system of work in place to manage psychosocial hazards, employee’s psychological wellbeing suffers & this resulted in negative consequences to organizations by way of increase cost through sickness absenteeism & high staff turnover. Clarke and Cooper (2004) define psychosocial hazards as aspects of work design and the organization and management of work and their social and organizational contexts that have the potential for causing psychosomatic harm (Clarke & Cooper, 2004). To identify the stressors behind occupational stress, we must first understand the leading underlying causes of the stressors. Kerr, McHugh and McCrory (2009) in their article HSE Management Standards and Stressrelated Work Outcomes recommended the use of United Kingdom Health and Safety Executive (HSE) Management Standards as it highlights six critical areas of work design that, if not adequately managed, are associated with reduced well-being and health, low productivity as a whole and increased sick leave. The six key areas are Demands, Control, Support, Relationships, Role and Change (Kerr, McHugh, & McCrory, 2009). 3. RESEARCH OBJECTIVES This research aims to ascertain the incidence of occupational stress among Polytechnic academicians during COVID-19 pandemic using modified HSE UK Management Standards. HSE UK Management Standards is a tool that helps manage stress-related work outcomes through an emphasis in six critical areas of work design. In essence, this research addresses four research objectives: 1. To ascertain the incidence of Occupational Stress amongst Polytechnic academicians using modified HSE UK Management Standards during Covid-19 pandemic. 2. To identify the stressors leading to incidences of Occupational Stress amongst Polytechnic academicians during Covid-19 pandemic. 134

3. To identify the highest risk level stressors causing Occupational Stress amongst Polytechnic academicians. 4. To identify the adverse health effects suffered by Polytechnic academicians from Occupational Stress 4. LITERATURE REVIEW To further understand the impact of occupational stress on employees during a pandemic, more research must be done to whittle down the uncertainties around it. A deep understanding of HSE Management Standards Indicator Tool is needed as it is used as the basis of this paper albeit with a modification to accommodate for constrains that it cannot tolerate which in this case related to work during a pandemic setting. The six key areas of work design that are posited as the basis of HSE UK Management Standards Indicator Tool covers all the psychosocial-environmental variables that are correlated to stress in the workplace. A deep understanding of Occupational Stress theoretically is also a must to ensure data collected in the research does not deviate and are in tandem with the theory and hypothesis. The theories examined in this research are the Person-Environment Fit Model, Karasek's Job Demand-Control Model and the Effort-Reward Imbalance Model. Lastly, as this research fringes on the effect of working at home/telecommuting, it brushes upon the aspect of Work-Life Interface. Work-Life Interface being the intersection of the work environment and private life needs to be balanced as any disruptions to the balance will produce adverse effect mainly in the form of unnecessary and undue stress. 4.1 HSE UK Management Standards HSE Management Standards is an approach first developed by the United Kingdom Health and Safety Executive (HSE) as a way to reduce the level s of occupational stress amongst workers. Developed from Cox's factors of psychosocial, work and organisational factors, its initial aim was to reduce cases of absenteeism due to stress-related symptoms and underachievers who cannot perform well due to stress (Cousins, et al., 2004). However, since then, HSE UK Management Standards has undergoes refinement to demonstrate good health management practices at work through evidence-based, joint problem solving between management and employees through the risk management process. Cox’s interpretation for factors of psychosocial, work and organisational factors can be loosely defined as aspects of designs and management of work and its social & organisational contexts that are capable of eliciting psychological and/or physical harm (Leka, Cox, & Zwetsloot, 2008). The reason on why defining psychosocial factors can be challenging lies with facts that some researchers tend to interchange psychosocial factors with work organization & aspects of the individual (Regulies, 2019). However, with the case of HSE UK Management Standards, a commonly accepted six key areas has been identified such that it covers a large expanse of psychosocial factors. Despite there being a commonly accepted concord that define on what exactly are psychosocial hazards (the six key areas: Demands, Control, Support, Relationships, Role, and Change), however, Leka, Cox and Zwetsloot (2008) suggested that it should be of note that new elements of work’s aspects might give rise to new hazards, that are previously not identified in scientific publications. Standfeld, Head, & Marmot found that high job demands were a predictor of poor health functioning and psychiatric disorder (Standfeld, Head, & Marmot, 2000). This can be attributed to the fact that high job demands, especially in term of high workload, interact with control perceptions to affect the physical and medical health outcomes. The presence of stressors in the form of job demands causes medical symptoms of occupational stress in a phenomenon called psychosomatic disorders. Psychosomatic disorder is an amalgam of psychology, meaning of mind & behaviour and soma, meaning of the body, is a physical symptom that arises because of aggravation by mental factor. Thus, Management Standards has placed upon a set target for its effectiveness, which is at least 85% of employees indicated that they are capable of coping with all aspects of their work demands and there are systems in place to respond to any diverge of Management Standards and can respond to employees’ consternations. The second key area is a Work Control which has relationships with stress in term of perceptions and ability of an individual to cope with their work. Employees with a high degree of locus of control are found to be less prone to occupational stress as they believe they are in control with aspects of their work. Saufi, Leong, Chua, & Razali (2013) in their study noted that individuals with an external locus of control, who perceived they are not in control of important aspects of their work environment would find the work environment to be more threatening and stressful (Saufi, Leong, Chua, & Razali, 2013). Social Support meanwhile can be interpreted as the availability and quality of an employee's relationship with immediate superiors, co-workers, family and friends and the amount of favourable consideration and task assistance received from them (Mackay, Cousins, Kelly, Lee, & McCaig, 2004). The main stress factors involving organisational change among employees need 135

to 'rationalise' for example, staffing levels. Thus, these are accompanied by job insecurities and the increased burden of fewer employees to do more work (Mackay, Cousins, Kelly, Lee, & McCaig, 2004). 4.2 Occupational Stress Model Occupational Stress touches upon many different fields of studies. From the biological field of studies to psychological and even engineering. In the biological perspective, stress is considered as the internal, nonspecific response of the body's physiological systems to physical and psychological demands made upon it (Chen, 2001). Stimulation to either the sympathetic-adrenal medullary system or the hypothalamic-pituitaryadrenocortical axis utilising physical or psychological will elicit a biological response as well as psychosomatic response. The engineering perspectives put stress as a total number of load and level of demand on the system. In this case, it can be said that stress is events that signal significant life changes in the individual affected by the stress. It has been established earlier that Occupational Stress touches upon many different fields of studies. This complexity has led to the development of several theoretical models of how Occupational Stress develops. Among such literature that described on Occupational Stress are Karasek's Job Demand Control Model (Choi, et al., 2010), Person-Environment (PE) Fit Model (Caplan, 1987), and Effort-Reward Imbalance (Chen, 2001) 4.2.1 Job Demand Control Model Job Demand Control Model's basic premises that high strain jobs are jobs in which its employees are subjected to high levels of work demands, but at the same time has little to say (control) in their work (Kain & Jex, 2010). This model, developed by Robert Karasek, is designed to predict harmful strains of job demands and job controls to manage occupational stress better as caused by the strains. Even though it is used to investigate the interaction between job demands and job control towards producing strains, however, Karasek argued that statistically significant interaction between the variables is unnecessary for the model to function as job demands and job control each exert independent main effects on the strain. Be that as it may, this model's use must be with caution as Kain & Jex (2010) cautioned in their paper as the model does not consider individual characteristics of the employees. Figure 4.1 shows the premise of Job-Demand Control Model. Figure 4.1: Karasek's Job Demand Control Model (Kain & Jex, 2010) 4.2.2 Person-Environment (PE) Fit Model Person-Environment (PE) Fit Model posits that when an individual and his work environment characteristics are compatible, that individual's attitudes and behaviours are likely to be positive (Caplan, 1987). On the contrary, any misfit between the individual and his environment will likely cause dysfunctional attitudes and behaviour. This mismatch between an individual and his work environment will foment stress upon the individual. PE Fit Model can be divided into four domains, as is commonly found in any work environment. They are Person-Job Fit, Person-Organization Fit, Person-Group Fit and Person-Person Fit. These domains are congruent with the basis presented in HSE UK Management Standards: Job Demand, Job Control, Support, Relationship, Role and Change. Whenever there is a discrepancy between the demands of the job and the ability for the individual to meet those demands, or, a conflict between organizational culture and the individual or even discord in the relationship between the individual and his work colleague, strains will be produced and thus be a factor in Occupational Stress. One of the salient points of Person-Environment Fit is the needs-supplies. Needs-supplies is the degree to which employee needs (need to use skills and abilities, needs for income, needs for a sense of belonging and participation) are met by the work environment's supplies and opportunities to satisfy those needs. (Caplan, 1987).PE Fit Models is the Person-Organization Fit Model model predicates that values as the most important things in the larger PE Fit Model (Chatman, 136

1989). Chatman (1989) also implies that as Person-Organization Fit is the harmony between personal values of that particular employee and the norms and values of that organisation (meaning the norms and values shared and hold to belief among all other employees), thus Person-Organization Fit can be achieved either by a rigorous employee selection process, where the organisation accept only people whose values match those of the organisation or by ensuring that the current employees relationships either with their superiors or their peers are in a good state. This may be in the form of increased contract duration with the organisation, feeling of satisfaction in doing a job that fit their skills and needs as well as having a sense of competence and being able to succeed in doing a good task. However, Schneider (1987) warned that high levels of fit in the Person-Organization Fit Model are not a good thing both towards the employees and the organisations (Schneider, 1987). This is because achieving extremely high levels of fit may causes inefficiency to be introduced into individuals and organisations' association. 4.2.3 The Effort-Reward Imbalance Model The Effort-Reward Imbalance Model figure 4.2 originated from the discipline of medical sociology and emphasizes on the effort and the reward structure of work (van Vegchel, de Jonge, Bosma, & Schaufeli, 2005). This model's premises that work-related benefits depend upon a reciprocal relationship between efforts and rewards at work (Siegrist, 1996). The efforts mentioned here stand for the job demands and job obligations imposed by the employer to the employee, whilst the rewards constitute as the money, job security, sense of belonging and achievement as well as esteem given to the employee as means of recognition of service, effort, or achievement rendered. Any reciprocity deficit between efforts and rewards, for example, high efforts but low rewards work will elicit strain reactions. Moreover, prolonged imbalance will cause sustained strain reactions. So, working hard on a difficult task and achieves targeted results but are not rewarded with commensurate gratuity and award is an example of a stressful imbalance. Furthermore, overcommitment, an intrinsic characteristic, can aggravate the situation. For example, highly dedicated employees will elicit more strain reactions to Effort-Rewards Imbalance when compared to less dedicated employees. Figure 4.2: Effort-Reward Imbalance Model (van Vegchel, de Jonge, Bosma, & Schaufeli, 2005) 4.3 Yerkes-Dodson Law The use of Yerkes-Dodson Law, an animal behaviour modification experiment in 1907 with occupational stress, in particular, the demand aspect of it started when the original experiment paper was cited in psychology journals and its premise; “optimum motivation for a learning task decreases with increasing difficulty” were found to hold true by Hans Eysenck in his 1995 article for the relationship between anxiety and task performance in humans (Corbett, 2015). The Yerkes-Dodson Law premise can further be explained that arousal or stress has an empirical relationship. What this means is that performance will increase alongside arousal/stress up until a certain point before it regresses as humans started to unable to cope with the stress. The law, best illustrated by the famous bell-shaped curve which increases and then decreases with higher levels of arousal as pictured in Figure 4.3 below. Figure 4.3: Yerkes-Dodson Law 137