Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026161Course Code: TPQ 3783Course Name: INFERENS STATISTIK STATISTICAL INFERENCECredit Hour: 3Pre-requisite: NoneCourse SynopsisThis course focuses on the fundamentals of statistical inference for population parameters based on a general decision theoretic framework, which covers estimation and hypothesis testing. Concepts, methods, and theory are emphasised.Course Learning OutcomesAt the end of this course, students are able to:1. APPLY the concept of probability in relation and concept of sampling error. (C3)2. EXPLAIN the concept of point and confidence interval estimation for given parameters. (C2, A4)3. DESIGN an appropriate hypothesis testing based on given statistical problems. (C5, P7)References1. Hogg, R.V., Tanis, E.A., & Zimmerman, D.L. (2019). Probability and Statistical Inference. Tenth Edition. Essex, United Kingdom: Pearson.2. Miller, M. & Miller, I. (2012). John E. Freund's Mathematical Statistics with Applications. Eight Edition. Essex: Pearson.3. Mukhopadhyay, N. (2006). Introductory Statistical Inference. New York: Chapman & Hall/CRC.4. Casella, G. & Berger, R. (2001). Statistical Inference. Second Edition. Kentucky: Duxbury Press.5. Silvey, S.D. (2003). Statistical Inference. New York: Chapman & Hall/CRC.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026162Course Code: TPQ 3433Course Name: STATISTIK BAGI PENYELIDIKAN OPERASI STATISTICS FOR OPERATIONS RESEARCH Credit Hour: 3Pre-requisite: NoneCourse SynopsisThis course covers topics from types of data, describing data sets graphically and numerically, commonly used probability distribution, sampling distribution and confidence interval, hypothesis testing, analysis of variance, goodness of fit and contingency table and finally regression and correlation. This course will focus more on the procedures of the analysis and interpretation of results. Software application is strongly emphasised.Course Learning OutcomesAt the end of this course, students are able to:1. IDENTIFY the theoretical foundations of basic concepts in probability and statistics. (A4)2. APPLY the theoretical foundations of the knowledge to model pertaining to related problems. (C3)3. SOLVE the mathematical models using various tools and methods from the theoretical foundations on basic concepts in probability and statistics together with statistical software, in order to interpret the results from the analysis. (C3)References1. Carlson, K. A. and Winquist, J. R. (2021). An Introduction to Statistics, An Active Learning Approach, 2nd Edition. SAGE Publications, Inc. 2. Navidi, W. (2015). Statistics for Engineers and Scientists. Fourth Edition. New York: McGrawHill Education.3. Bluman, A.G. (2018). Elementary Statistics. Tenth Edition. New York: McGraw-Hill Education.4. Reid, H.M. (2014). Introduction to Statistics: Fundamental Concepts and Procedures of Data Analysis. New York: Sage. 5. Bluman, A.G. (2013). Elementary Statistics. Sixth Edition. New York: McGraw-Hill Education.6. Montgomery, D.C., Runger, G.C. & Hubele, N.F. (2011). Engineering Statistics. Fifth Edition. Hoboken, New Jersey: John Wiley & Sons, Inc.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026163Course Code: TPQ 3793Course Name: SIRI MASA DAN RAMALAN TIME SERIES AND FORECASTING Credit Hour: 3Pre-requisite: NoneCourse SynopsisThis course introduces the art and science of forecasting. Students will be guided on the proper procedures in the forecasting works. Topics include forecasting techniques, forecasting process, understanding time series, univariate modelling techniques, econometric modelling, Box-Jenkins methodology and evaluating the models.Course Learning OutcomesAt the end of this course, students are able to:1. DESCRIBE the forecasting process, concept of stationarity, basic stationary time series models and the autocovariance and autocorrelation functions for basic time series models. (C2, A1, P1)2. DEVELOP the forecasting models such as the regression models, the exponential smoothing models and Autoregressive Integrated Moving Average (ARIMA) models to forecast the data. (C5)3. ANALYSE data and forecasting models using statistical methods. (C4)References1. Hyndman, R.J. & Anthanasopoulos, G. (2018). Forecasting Principles and Practice. Second Edition. Melbourne: Otexts.2. Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2015). Introduction to Time Series Analysis and Forecasting. John Wiley & Sons. 3. Silvia, J., Iqbal, A., Bullard, S., Watt, S. & Swankoski, K. (2014). Economic and Business Forecasting: Analysing and Interpreting Econometric Results. Hoboken, New Jersey: John Wiley & Sons, Inc. 4. Ord, J.K. & Fildes, R. (2013). Principles of Business Forecasting. Mason, Ohio: Cengage Learning.5. Mohd Alias Lazim. (2011). Introductory Business Forecasting: A Practical Approach. Third Edition. Shah Alam, Selangor: UPENA.6. Brockwell, P.J. & Davis, R.A. (2002). Introduction to Time Series and Forecasting. Second Edition. New York: Springer-Verlag.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026164SINOPSIS KURSUS TERAS SAINS DATACourse Code: TPD 3833Course Name: ANALITIK DATA RAYABIG DATA ANALYTICSCredit Hour: 3Pre-requisite: NoneCourse SynopsisThis course aims to provide an overview of data analytics and modeling for handling of massive databases. The students will learn on howo to apply machine learning techniques and methods that arise in data analytic applications. Toward the end, the student will learn and practice data analytic techniques in the data science process including selecting a model, training a model, validating a model, and predicting new observations. Distributing data storage and processing with frameworks such as Hadoop, Spark, and Radoop will also be discussed and presented.Course Learning OutcomesAt the end of this course, students are able to:1. DESCRIBE the basic theory and concepts of big data analytics and the data science process. (C2, A1)2. APPLY data science process and machine learning algorithms to solve real world problems (e.g. classification and clustering). (C3)3. BUILD data analytics models to solve real-world problems (e.g. by applying machine learning techniques and using data analytics tools). (P7)References1. 1. Jeffrey S. Saltz, Jeffrey Morgan Stanton (2024). An Introduction to Data Science With Python 1st Edition. SAGE Publications, Inc.2. Laura Igual, Santi Seguí (2024), Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications (Undergraduate Topics in Computer Science) 2nd ed. 2024 Edition, Springer3. Nitin Kumar Yadav (2024). Big Data Analytics. Noteskaro Inc.\"
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026165Course Code: TPD 3853Course Name: PENTADBIRAN AWAN DAN PUSAT DATA CLOUD AND DATA CENTRE ADMINISTRATIONCredit Hour: 3Pre-requisite: NoneCourse SynopsisThis course provides students with in-depth knowledge and practical skills in administering cloud environments and managing data centre operations. Students will explore cloud computing concepts, service and deployment models, virtualization, storage systems, resource management, and infrastructure automation. The course also covers physical and virtual data centre components, including power, cooling, hardware, and network architectures. Emphasis is placed on deploying, monitoring, and securing cloud platforms and optimizing data centre resources for scalability and reliability.Course Learning OutcomesAt the end of this course, students are able to:1. DESCRIBE the core concepts, components, and service models of cloud computing and data centres. (C2)2. ANALYSE cloud infrastructure and virtualized environments using relevant tools and platforms.(C4)3. EVALUATE data centre operations in terms of performance, scalability, and security. (C5)References1. Mulder, J., 2024. Multi-Cloud Administration Guide: Manage and Optimize Cloud Resources across Azure, AWS, GCP, and Alibaba Cloud. Mercury Learning & Information.2. Nazar Zadeh, N., 2024. Data Centre Management. Toronto Academic Press / Arcler Press.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026166Course Code: TPD 3813Course Name: KONSEP PANGKALAN DATA DATABASE CONCEPTCredit Hour: 3Pre-requisite: NoneCourse SynopsisThe course covers Database Systems and File Systems, Relational Data Modeling, SQL, E-R Modeling, Normalization, Transaction and Concurrency Control, Database Design and Implantation. This course also discussed the latest and future trends in computer databases. A Database Management System (DBMS) will be introduced, and the DBMS development techniques will be exposed to the students for practical sessions and coursework.Course Learning OutcomesAt the end of this course, students are able to:4. IDENTIFY database management concept and user requirements/views and conceptual data model including all entities, relationships, attributes, and business rules. (C1)5. CONDUCT database design and normalization techniques based on the user requirements.(P4)6. DEVELOP a prototype of a database driven system. (A4)References3. Coronel, C., & Morris, S. (2018). Database systems: design, implementation, & management. Cengage Learning. 13th Edition.4. Connolly, T.M. & Begg, C.E. (2015). Database Systems: A Practical Approach to Design, Implementation and Management. Sixth Edition. Essex: Pearson.5. Molina, H.G., Ullman, J.D. & Widom, J. (2008). Database Systems: The Complete Book.Second Edition. New York: Prentice Hall.6. Elmasri, R. & Navathe, S.B. (2010). Fundamental of Database Systems. Sixth Edition. New York: Addison-Wesley.7. Coronel, C., Rob, P. & Morris, S. (2009). Database Systems: Design, Implementation, and Management. Ninth Edition. New York: Thomson Learning.8. Date, C.J. (2003). An Introduction to Database System. Eighth Edition. Singapore: AddisonWesley.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026167Course Code: TPD 3843Course Name: PENGURUSAN KUALITI DATADATA QUALITY MANAGEMENTCredit Hour: 3Pre-requisite: NoneCourse SynopsisThis course introduces students to the fundamental principles and practices of Data Quality Management in the context of Operations Research (OR) and Data Science. Students will explore the essential dimensions of data quality, the role of standards and frameworks, and the impacts of poor data on analytics-driven decision-making. The syllabus integrates both conceptual foundations and practical case studies, equipping students with skills in data profiling, measurement, cleansing, integration, and quality assurance. Emphasis is placed on real-world applications, including tools and automation relevant to contemporary data-intensive environments. By the end of the course, students will be able to critically assess, monitor, and improve data quality to support robust, accurate, and ethical analysis and decision processes in organizations.Course Learning OutcomesAt the end of this course, students are able to:1. EXPLAIN fundamental principles, dimensions, and frameworks of data quality management in operational and data science contexts (C4)2. PERFORM data profiling, measurement, and cleansing using industry-relevant tools and techniques to improve data integrity (P2)3. ANALYZE and propose solutions for common data quality issues affecting organizational decision-making and analytics outcomes.References1. King, T. and Schwarzenbach, J. (2020). Managing Data Quality: A practical guide.BCS, The Chartered Institute for IT Publisher.2. Hawker, R. and Askham, N.. (2023). Practical Data Quality: Learn practical, real-world strategies to transform the quality of data in your organizations: Statistical Principles of Research Design and Analysis. Packt Publishing.3. Southekal, P. (2023). Data Quality:Empowering Business with Analytics and AI. First Edition. Wiley Publisher.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026168Course Code: TPD 3823Course Name: ASAS KECERDASAN BUATAN FUNDAMENTALS OF ARTIFICIAL INTELLIGENCECredit Hour: 3Pre-requisite: NoneCourse SynopsisThe course aims to introduce the principles, methods and techniques used in Artificial Intelligence and Expert Systems. It exposes students to search techniques, logic, knowledge representation and reasoning, intelligent agents, and machine learning. Programming platforms such as MATLAB will be used in practical sessions and coursework.Course Learning OutcomesAt the end of this course, students are able to:4. DEFINE fundamental concepts and techniques in Artificial Intelligence by studying key AI methodologies and approaches. (C1, PLO1)5. DEMONSTRATE a theoretical understanding to reason about the behavior and functioning of Artificial Intelligence systems. (C2, PLO2)6. APPLY Artificial Intelligence concepts to develop and implement intelligent system applications. (C3A, PLO3)References4. Russell, S. J. & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. 4th Edition. New Jersey: Prentice Hall. 5. Tom Taulli. (2019). Artificial Intelligence Basics: A Non-Technical Introduction: APress6. Anuradha, J, Tripathy, B.K., I. (2018). Internet of things (IoT): technologies, applications, challenges and solutions. CRC Presss: Taylor & Francis7. Bratko, I. (2015). PROLOG Programming for Artificial Intelligence. 4rd ed. Singapore: Addison Wesley.8. Negnevitsky, M. (2016). Artificial Intelligence: A Guide to Intelligent Systems. 3rd ed. Addison Wesley Pearson Education.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026169Course Code: TPD 3713Course Name: PEMBELAJARAN MESIN UNTUK SAINS DATA MACHINE LEARNING FOR DATA SCIENCE Credit Hour: 3Pre-requisite: NoneCourse SynopsisMachine learning is the force behind many recent revolutions in computing. It is concerned with the creation of computer systems that are capable of understanding and inferring insights from unseen information so that they can automatically learn from experience to continuously improve their performance. This course provides students with the knowledge and skills to apply machine learning techniques to analyze and gain insights from real-world data. The outcomes will contribute to both pattern recognition and machine learning to predict an outcome and decide on a suitable course of action.Course Learning OutcomesAt the end of this course, students are able to:1. IDENTIFY dataset for Machine Learning process and output. (C2) 2. APPLY Machine Learning algorithms for supervised and unsupervised learning (C3D)3. ANALYSE the Machine Learning model and output values correctly. (C3E)References1. Sugiyama, M. (2016). Introduction to statistical machine learning. Morgan Kaufmann.. 2. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.3. Alpaydin, E. (2020). Introduction to machine learning (4th ed.). MIT Press.4. Mohri, M., Rostamizadeh, A., & Talwalkar, A. (2018). Foundations of machine learning (2nd ed.) MIT Press.5. Marsland, S. (2014). Machine learning: An algorithmic perspective (2nd ed.). Chapman and Hall/CRC.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026170SINOPSIS KURSUS ELEKTIF PENYELIDIKAN OPERASICourse Code: TPQ 3733Course Name: EKONOMETRIK ECONOMETRICS Credit Hour: 3Pre-requisite: NoneCourse SynopsisThis course will introduce the students to the theory and applications of econometric analysis. The course has a strong applied emphasis. This is an empirically-based course in which students will develop hypotheses grounded in theory and then test those hypotheses using data and statistical methods. The first part of the course provides an introduction to basic econometric concepts and data analysis techniques, such as descriptive statistics, correlation and regression, probability, chance variability, and sampling. The second part of the course covers hypothesis testing, the basic regression theory and techniques used in empirical work which include simple and multiple regression models, dummy variables, heteroskedasticity, and methods of instrumental variables.Course Learning OutcomesAt the end of this course, students are able to:1. IDENTIFY appropriate statistical technique to test hypotheses for different types of economic and econometric variables. (C1)2. DEVELOP econometrically testable hypotheses based upon economic theory. (C5)3. DEMONSTRATE application of appropriate econometric methods to test an economic theory. (C3)References2. Wooldridge, J.M. (2016). Introductory Econometrics: A Modern Approach. Sixth Edition. Boston: Cengage Learning.3. Hayashi, F. (2000). Econometrics. New Jersey: Princeton University Press. 4. Baltagi, B.H. (2011). Econometrics. Fifth Edition. Berlin, Heidelberg: Springer.5. Westhoff, F. (2013). An Introduction to Econometrics: A Self-contained Approach. Cambridge: MIT Press.6. Stock, J.H. & Watson, M.W. (2015). Introduction to Econometrics. Third Edition. New York: Pearson.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026171Course Code: TPQ 3763Course Name: PENGENALAN KEPADA PENGURUSAN BAHAN INTRODUCTION TO MATERIALS MANAGEMENTCredit Hour: 3Pre-requisite: NoneCourse SynopsisThe course on materials management provides an in-depth understanding of managing materials and production processes effectively. It starts with an introduction to materials management principles, including inventory control, procurement, and logistics. Students then explore production planning systems and master scheduling, learning to align production plans with organisational goals and manage material requirements. Capacity management and production activity control are examined to optimise resource use and monitor production performance. The course also covers purchasing strategies, focusing on supplier selection and procurement, and concludes with forecasting and demand management techniques to align supply with anticipated demand.Course Learning OutcomesAt the end of this course, students are able to:1. DESCRIBE the key principles and practices of materials management, including inventory control, procurement, and logistics, to effectively manage materials and support production operations. (C2, A1)2. OPTIMISE production plans using master scheduling and material requirements planning (MRP) techniques, along with capacity management and production activity control, to meet organisational objectives. (C5)3. USE forecasting methods and demand management techniques to predict market needs and apply purchasing strategies for timely, cost-effective material acquisition. (C3)References1. Chapman, S. N., Arnold, J. R. T., Gatewood, A. K., and Clive, L. M. (2023). Introduction to Materials Management 9th Edition. Pearson. NCCER (2019). Project Management Trainee Guide, 3rd Edition. Pearson. 2. Anil Kumar, S. (2020). Production and operations management. New Age Intl., New Delhi. 3. Chapman, S. N., Arnold, J. R. T., Gatewood, A. K., and Clive, L. M. (2017). Introduction to Materials Management 8th Edition. Pearson. 4. Arnold, J. R. T., Chapman, S. N., and Clive, L. M. (2008). Introduction to Materials Management6th Edition. Pearson.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026172Course Code: TPQ 3773Course Name: PENGURUSAN PROJEK PROJECT MANAGEMENT Credit Hour: 3Pre-requisite: NoneCourse SynopsisThis course explores the essential role of project management in helping organisations achieve their goals across various industries. Students will explore key project management methodologies and learn to assess and apply suitable approaches for different projects. Essential scheduling techniques, including network diagrams, critical path analysis, and advanced methods like lagging, leading, and crashing, are covered to enhance project efficiency and meet deadlines effectively. Additionally, the course delves into resource management strategies, teaching students how to plan, allocate, and optimise resources throughout the project lifecycle. Techniques such as resource leveling and monitoring are emphasised to address constraints and ensure optimal resource utilisation. Through real-world case studies and practical exercises, students will gain the skills necessary to manage projects efficiently and drive successful outcomes. Additionally, they will learn to utilise project management software to address complex problems.Course Learning OutcomesAt the end of this course, students are able to:1. DESCRIBE the importance and role of project management in achieving organisationalobjectives across various industries. (C2, A1)2. DEVELOP and analyse network diagrams, estimate activity durations, determine the critical path, and apply techniques like lagging, leading, and crashing to enhance scheduling efficiency. (C5)3. PLAN and allocate resources strategically, addressing constraints and monitoring utilisation to ensure optimal resource management and project success. (C5)References1. Jeffrey, K. P. (2019). Project Management: Achieving Competitive Advantage, 5th Edition. Pearson. 2. NCCER (2019). Project Management Trainee Guide, 3rd Edition. Pearson. 3. Avraham S. and Moshe R. (2017). Project Management: Processes, Methodologies, and Economics, 3rd Edition. Pearson.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026173SINOPSIS KURSUS ELEKTIF SAINS DATACourse Code: TPD 3423Course Name: KECERDASAN PERNIAGAAN DENGAN VISUALISASI DATABUSINESS INTELLIGENCE WITH DATA VISUALISATIONCredit Hour: 3Pre-requisite: NoneCourse SynopsisThis course is designed to equip participants with essential skills in effectively interpreting and presenting data. Throughout the course, students will learn the core principles of data visualization, including how to choose the appropriate visual representations for different data types and how to craft compelling data-driven narratives. The course will also introduce popular data visualization tools such as Microsoft Excel, Power BI, and Tableau. In addition to visualization techniques, students will explore reporting methods to create clear, actionable reports for stakeholders. By the end of the course, students will have the ability to analyze and communicate data effectively, making it suitable for professionals in fields such as data analytics, marketing, finance, or management who wish to enhance their data presentation skills.. Course Learning OutcomesAt the end of this course, students are able to:1. EXPLAIN the importance of choosing the correct visual representation for different types of data and how effective data visualization can enhance data-driven decision-making. (C2) 2. APPLY basic visualization techniques to create charts, graphs, and other visual elements using data visualization tools, ensuring clarity and accuracy in the presentation. (A3)3. DEVELOP comprehensive reports that incorporate multiple visualizations to effectively convey complex data stories to different audiences, tailoring the content to meet specific stakeholder needs. (A4)References1. Alex, K. and Maxim, Z. (2024). Data Visualization with Microsoft Power BI. O'Reilly Media, Inc. 2. Ryan, L. (2023). Visual Analytics Fundamentals: Creating Compelling Data Narratives with Tableau. United Kingdom: Addison Wesley Professional. 3. Ryan, L. (2023). Visual Analytics Fundamentals: Creating Compelling Data Narratives with Tableau. United Kingdom: Pearson Education. 4. P. (2023). Data Visualization with Python: Exploring Matplotlib, Seaborn, and Bokeh for Interactive Visualizations. India: BPB.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026174Course Code: TPD 3433Course Name: JAMINAN DAN KESELAMATAN PENGHANTARAN DATADATA TRANSMISSION ASSURANCE AND SECURITYCredit Hour: 3Pre-requisite: NoneCourse SynopsisThis course is intended to help students to gain fundamental and comprehensive understanding of information security. This course focuses on an overview of major information security issues, technologies, and approaches. Students who successfully completed this course will have a concept and knowledge of the Common Body of Knowledge (CBK) Security Domains.Course Learning OutcomesAt the end of this course, students are able to:1. DESCRIBE the terminologies use in cryptology and the basic model of public key cryptosystems and digital signature schemes. (C2) DESCRIBE the Common Body of Knowledge (CBK) Security Domains. (C2)2. ANALYSE the issues with regards to information security, risk management, security architecture, security design and Business Continuity and Disaster Recovery Planning. (C4)3. EXPLAIN case scenarios given in the areas of Legal, Regulations, Compliance and Investigations. (A3)References1. Panos Louridas. (2024). Cryptography (The MIT Press Essential Knowledge series). The MIT Press. \"1. Whitman, M.E., Mattord, H.J., 2018. Principles of Information Security. 6th edn. Cengage Learning.2. Easttom, Chuck. 2019. System forensics, investigation, and response. 3rd edn. Jones & Bartlett Learning.3. Jennifer H. Elder , and Samuel F. Elder. 2019. Faster disaster recovery : the business owner's guide to developing a business continuity plan. John Wiley & Sons.4. Sean-Philip Oriyano, Michael G. Solomon. 2020. Hacker techniques, tools, and incident handling. 3rd edn. Jones &Bartlett Learning.\"
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026175Course Code: TPD 3773Course Name: PEMPROSESAN DAN ANALITIK IMEJ IMAGE PROCESSING AND ANALYTICSCredit Hour: 3Pre-requisite: NoneCourse SynopsisImage processing and analytics course studies on fundamentals of digital image and data reside in digital images. Topics discussed includes digital images structures, algorithm and methodology of image processing, digital image extraction, and interpret data from digital images. Knowledge gained from this course are the structure of digital images, digital images technologies, digital images techniques, and constructing a digital image. Skills acquired from this course are investigation on digital images data, images analysis, and digital images data description.Course Learning OutcomesAt the end of this course, students are able to:4. DESCRIBE the structure of a digital image including metadata. (C2)5. APPLY an appropriate image processing method based on data case. (C3A)6. INTERPRET data discovered from digital images extraction and analysis. (C3D)References1. Ambrósio, P. E. (2022, April 20). Digital image processing applications. IntechOpen.2. Petrou, M. M. P., & Kamata, S. (2021, March 22). Image processing dealing with texture. Wiley.3. Rafael C. Gonzalez & Richard E. Woods (2018), Digital Image Processing, 4th edition, Pearson Bernd Jähne (2022), Digital Image Processing and Image Formation 7th ed. 2022 Edition, Springer.4. Ravishankar Chityala & Sridevi Pudipeddi (2022), Image Processing and Acquisition using Python, Chapman & Hall/CRC.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026176Course Code: TPD 3413Course Name: APLIKASI BERORIENTASIKAN OBJEK OBJECT-ORIENTED APPLICATIONCredit Hour: 3Pre-requisite: NoneCourse SynopsisObject Oriented Application course introduces the basic concepts of object-oriented programming and using Python language to deliver data solution (Analysis, Processing and Visualization). Topics covered in this course from getting familiar with Python programming environment to developing a basic python computer program. The database equipped application also covered in this course. Learners will be able to produce a basic but comprehensive python computer program for data processing case.Course Learning OutcomesAt the end of this course, students are able to:1. KNOW basic concepts of a high level programming language using object oriented programming correctly. (C1, C1)2. ADAPT knowledge with the basic notions and techniques to develop the algorithm and basic object oriented programming language. (C3A, P6)3. DEMONSTRATE a computer programme with object oriented knowledge correctly and effectively. (C3D, P4)References1. Y Daniel Liang (2022) Introduction to Python Programming and Data Structures, 3rd edition,Pearson.2. Dr. Muneer Ahmad Dar (2020). JAVA Programming Simplified: JAVA Programming Simplified3. Matt Weisfeld (2019). Object-Oriented Thought Process, The, 5th Edition, Addison-Wesley.4. Herbert Schildt (2018). Java: A Beginner's Guide, Eighth Edition5. Gaddis, Y. (2010). Starting Out with Java: From Control Structures Through Objects. Fourth Edition. New York: Addison-Wesley.6. Malik, D.S. (2012). Java Programming: From Problem Analysis to Program Design. Fifth Edition. New York: Course Technology Cengage Learning.7. Liang, Y.D. (2011). Introduction to JAVA Programming. Ninth Edition. New Jersey: Prentice Hall. 8. Thomas, C.W. (2010). An Introduction to Object-Oriented Programming with Java. Fifth Edition. New York: McGraw-Hill.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026177SINOPSIS KURSUS ELEKTIF PROGRAM BERSAMACourse Code: TPB 3712Course Name: VISUALISASI DATA DENGAN CANVADATA VISUALISATION WITH CANVACredit Hour: 2Pre-requisite: NoneCourse SynopsisThis course introduces students to the art and science of data visualisation through a project-based learning approach using Canva. Students will explore visual storytelling techniques, chart design principles, and the use of Canva’s powerful layout and presentation tools to create compelling, data-driven outputs. Working on real-world problems and datasets, students will progressively design and refine their own infographic and presentation projects. The course emphasizes handson experience, critical thinking, and effective communication, culminating in a final project presentation where students showcase their visualisation solutions to specific audiences.Course Learning OutcomesAt the end of this course, students are able to:1. APPLY appropriate data visualisation techniques and tools to create meaningful and visually engaging graphics using Canva. (C3)2. PRESENT data-driven visuals effectively using Canva to communicate insights clearly to a target audience. (C3, C5, A2)References1. Reynolds, G. (2020). Presentation Zen: Simple Ideas on Presentation Design and Delivery(3rd Edition). New Riders. 2. University of York. (2019, November). Creative PowerPoint. Information Services, Universityof York. Retrieved from https://www.york.ac.uk/it-services/training
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026178Course Code: TPB 3722Course Name: ANALITIK DATA DALAM KEWANGANDATA ANALYTICS IN FINANCECredit Hour: 2Pre-requisite: NoneCourse SynopsisTo provide a foundation in financial analytics in order to handle complex financial data, build advanced analytical models and deliver effective visualization product and comprehensive reports.Course Learning OutcomesAt the end of this course, students are able to:1. DESCRIBES fundamental concepts and ethical considerations in financial data analytics including financial datasets, risk-return metrics and asset portfolios. (C2)2. APPLY financial analytics techniques and appropriate tools or programming languages. (C3/P4)3. ANALYSE financial risk across various financial assets to support informed financial decision-making. (C4)References1. Argimiro Arratia (2014), “Computational Finance An Introductory Course with R”, AtlantisPress, ISBN 978-94-6239-069-02. Bernhard Pfaff (2013),“Financial risk modelling and portfolio optimization with R”, Wiley, ISBN978-0-470-97870-23. Cairns, A.J. G (2004), “Interest Rate Models: An Introduction”, Princeton University Press,ISBN:97806911189494. Christian Gourieroux & Joann Jasiak (2002), “Financial Econometrics: Problems, Models, andMethods”, Princeton University Press , ISBN: 97806910887235. David Ruppert (2011),“Statistics and Data Analysis for Financial Engineering”, Springer, ISBN978-1-4419-7786-16. Duffie, D. and Singleton, K.J (2003), “Credit Risk: Pricing, Measurement, and Management”,Princeton University Press, ISBN: 9780691090467\"
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026179Course Code: TPB 3732Course Name: EKPLORASI DATA DENGAN EXCELDATA EXPLORATION WITH EXCELCredit Hour: 2Pre-requisite: NoneCourse SynopsisThis course introduces students to the powerful features of Microsoft Excel in a fun and engaging way. Students will learn to create, format, analyse, and visualise data using real-life examples. The course empasises hands-on activities to develop spreadsheet skills for academic, business, and personal use.Course Learning OutcomesAt the end of this course, students are able to:1. Apply essential Excel formulas and functions to perform data calculations.2. Analyse and visualise data using tables, charts, and PivotTables.3. Create well-organised and professional spreadsheets for academic or practical tasks.References1. Angela Monaghan. 2017. Rolls-Royce trioplead guilty to corruption chargers in US. Diestrakpada 9 Oktober 2018 daripada http://www.theguardian.com/business/2017/nov/08/rolls-roycetrio-plead-guilty-to-corruption-charges-in-us.2. Arkib Negara. 2013. Skim Cepat Kaya Pak Man Telo (1992). Diekstrak pada 22 Julai 2018daripada http:// arrkibnegara.blogspot.com/2013/09/skim-cepat-kaya-pak-man-tela1992.html.3. Association Certified Fraud Examiners (2013). report to the Nations on Occupational Fraudand Abuse 2013. GLOBAL Headquarters, Austin, USA.4. BBC. 2011. Nick Leeson apologies to Barings' boss for bank crash. Diekstrak pada 22 Julai2018 daripada http://www.bbc.co.uk/new/business-14424926
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026180Course Code: TPB 3742Course Name: ANALITIK KEUSAHAWANANENTREPRENEURIAL ANALYTICSCredit Hour: 2Pre-requisite: NoneCourse SynopsisThis course introduces students to the fundamentals of entrepreneurship through the lens of analytical thinking and data-informed decision-making. Students will explore how entrepreneurs analyze opportunities, markets, finances, and risks to create and grow ventures. Emphasis is placed on applying simple business analytics tools and entrepreneurial thinking in practical settings.Course Learning OutcomesAt the end of this course, students are able to:1. ANALYZE basic business problems using entrepreneurial frameworks and data tools.2. DEVELOP a simple business case with market, financial, and risk analysis.3. PRESENT entrepreneurial analysis in a structured format.References1. Camm, J. D., Cochran, J. J., Fry, M. J., & Ohlmann, J. W. (2024). Business analytics:Descriptive, predictive, prescriptive (5th ed.). Cengage Learning.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026181Course Code: TPB 3752Course Name: ANALITIK DATA IoTIOT DATA ANALYTICSCredit Hour: 2Pre-requisite: NoneCourse SynopsisThe Internet of Things (IoT) refers to a system of interrelated, internet-connected objects that can collect and transfer data over a wireless network without human intervention. This course will help the student to gain foundational knowledge of IoT as they explore the concepts, terms, and patterns of an IoT solution. Moreover, it will provide you with insights on the various data storage options available for your IoT solution. It will explore each option's specific purpose and guide you in selecting one or multiple options based on your architecture's needs .Additionally, as the course progresses, you will learn effective data processing and presentation methods for the IoT data you have collected and stored, ensuring a comprehensive understanding of IoT data management.Course Learning OutcomesAt the end of this course, students are able to:1. EXPLORE the architectural components of an IoT solution and how IoT is used in practice. (C2)2. EXPLAIN one or more approaches for implementing an IoT solution based on a use case scenario or problem statement. (C3D)3. EMPLOY data analysis and visualisation tools to present IoT data in a visually compelling and insightful manner for decision making. (C3E)References1. Perros, H. G. (2021). An introduction to IoT analytics. Chapman & Hall/CRC Data ScienceSeries.2. Madhavan, P. G. (2021). Data science for IoT engineers: A systems analytics approach3. Greengard, S. (2021). The internet of things (Revised and Updated ed.).4. Lea, P. (2020). IoT and edge computing for architects: Implementing edge and IoT systemsfrom sensors to clouds with communication systems, analytics, and security (2nd ed.).5. Hanes, D., Salgueiro, G., Grossetete, P., Barton, R., & Henry, J. (2017). IoT fundamentals:Networking technologies, protocols, and use cases for the Internet of Things (1st ed.).
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026182Course Code: TPB 3762Course Name: KAEDAH PENYELIDIKANRESEARCH METHODOLOGYCredit Hour: 2Pre-requisite: NoneCourse SynopsisThis course introduces undergraduate students to the fundamental principles and practices of research. It covers essential components such as research problem formulation, literature review, research design, data collection techniques, and methods of analysis. Students will explore both qualitative and quantitative research methodologies while gaining exposure to ethical considerations and academic writing standards. The course emphasizes hands-on learning through a group-based research proposal project, allowing students to develop critical thinking, teamwork, and effective communication skills necessary for academic and professional research. By the end of the course, students will be able to plan and present a research proposal in line with scholarly conventions.Course Learning OutcomesAt the end of this course, students are able to:1. IDENTIFY basic concepts of a high level programming language using object oriented programming correctly. (C1) Describe the fundamental concepts, types and ethical considerations in research. (C2)2. Construct a well-defined research problem with appropriate objectives and research questions. (C3)3. Prepare a research proposal using appropriate methodology, citation and academic writing skills.(C4)References1. David Ruppert (2015) Statistics and Data Analysis for Financial Engineering, 2nd edition,Springer.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026183Course Code: TPB 3772Course Name: SEJARAH MATEMATIKHISTORY OF MATHEMATICSCredit Hour: 2Pre-requisite: NoneCourse SynopsisThis course offers a historical overview of mathematics through the study of major ancient and classical civilisations. It examines key mathematical developments from Egyptian and Babylonian arithmetic and geometry, to Indian and Chinese numeral systems and algorithms, followed by the logical structure of Greek mathematics. The course also explores the significant contributions of Islamic scholars in algebra and astronomy, and concludes with European advances during the medieval and Renaissance periods. Emphasis is placed on understanding how mathematical ideas evolved within their cultural and historical contexts and how they shaped the foundations of modern mathematics.Course Learning OutcomesAt the end of this course, students are able to:1. DESCRIBE the historical development of mathematical ideas and theories from major ancient and classical civilisations, including the contributions of key mathematicians (C5, P7).2. ANALYSE different numeral systems and mathematical methods used by various cultures, and evaluate their impact on the evolution of mathematics (C3, C5, A2).References1. Victor J. K. (2024). History of Mathematics (4th Edition). Pearson. 2. Burton D. M. (2011). The History of Mathematics (7th Edition). Mc Graw Hill. 3. Cooke R. L. (2013). The History of Mathematics - A Brief Course (3rd Edition). Wiley
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026184SINOPSIS KURSUS PROJEK TAHUN AKHIRCourse Code: TPQ 3332Course Name: PROJEK TAHUN AKHIR I FINAL YEAR PROJECT ICredit Hour: 2Pre-requisite: NoneCourse SynopsisThis course aims to enable students to combine learnings from their previous courses of Operations Research with Data Science to develop a research or project proposal. The research proposal should comprise of problem statement, research aim, research objectives, scope and limitations of research, the significance of research, literature review and appropriate research methodology. The research methodology covers research designs (quantitative and mixed methods) and research methods which provide a detailed procedure or technique of data collection and analysis. Students will be required to obtain feedback from the supervisors about the research or project proposal. At the end of the project, students should hand in a written report and conduct a presentation.Course Learning OutcomesAt the end of this course, students are able to:1. ATTEND the departmental research seminars. (A3)2. PRODUCE a research proposal that contains the title of the research, problem statement, objectives, significance of research, literature review, research methodology, research Gantt chart and references. (C3)3. PRESENT the proposed research in a research proposal presentation. (C3, A2)References1. Sharifah Aishah Syed Ali, Fazilatulaili Ali dan Ruzanna Mat Jusoh (2022). Buku Panduan Projek Tahun Akhir Program Ijazah Sarjana Muda Penyelidikan Operasi dengan Sains Data. Kuala Lumpur: Fakulti Sains dan Teknologi Pertahanan, Universiti Pertahanan Nasional Malaysia.2. Zulkifly Mat Radzi (2009). Panduan Menulis Tesis Fakulti Sains dan Teknologi Pertahanan. Kuala Lumpur: Universiti Pertahanan Nasional Malaysia.3. Punch, K.F. (2006). Developing Effective Research Proposals. Second Edition. London: SAGE Publication Ltd.4. Ogden, T.E. & Goldberg, I.A. (2002). Research Proposals: A Guide to Success. Third Edition.California: Academic Press.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026185Course Code: TPQ 3344Course Name: PROJEK TAHUN AKHIR IIFINAL YEAR PROJECT IICredit Hour: 4Pre-requisite: Final Year Project I – TPQ 3332Course SynopsisThis course is a continuation of Final Year Project I. Students should be able to enhance their knowledge in analysing collected data, developing a mathematical model/solution approach, testing a model/solution approach using the data obtained/simulated data, analysing and discussing the results, and providing recommendations or suggestions for the problems stated in the research proposal. At the end of the semester, the students are required to submit a final year project report and to conduct a project presentation.Course Learning OutcomesAt the end of this course, students are able to:1. ATTEND departmental research seminars. (A3)2. PRODUCE a Final Year Project thesis that contains the title of the research, problem statement, objectives, significance of research, literature review, research methodology, results and discussion, conclusion and references. (C5)3. PRESENT the research findings in a Final Year Project presentation. (C5, A2)References1. Sharifah Aishah Syed Ali, Fazilatulaili Ali dan Ruzanna Mat Jusoh (2022). Buku Panduan Projek Tahun Akhir Program Ijazah Sarjana Muda Penyelidikan Operasi dengan Sains Data. Kuala Lumpur: Fakulti Sains dan Teknologi Pertahanan, Universiti Pertahanan Nasional Malaysia.2. Mohd Hazali Mohamed Halip, Nor Asiakin Hasbullah & Syahaneim Marzukhi. (2011). Panduan Penulisan Tesis dan Projek Sarjana Muda Sains Komputer. Kuala Lumpur: Jabatan Sains Komputer, Universiti Pertahanan Nasional Malaysia.3. Zarina Shukur. (2007). Menulis Dokumen Projek Perisian untuk Prasiswazah. Selangor: Kumpulan Sains Pengaturcaraan, UKM.4. Berndtsson, M., Hansson, J. Olsson, B. & Lundell, B. (2004). Planning and Implementing your Final Year Project – With Success! : A Guide for Students in Computer Science and Information Systems. London: Springer.5. Grätzer, G. (2014). Practical LaTeX. Switzerland: Springer.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026186SINOPSIS KURSUS LATIHAN INDUSTRICourse Code: TPQ 331CCourse Name: LATIHAN INDUSTRI INDUSTRIAL TRAININGCredit Hour: 12Pre-requisite: Completed Year TwoCourse SynopsisThis course provides an opportunity for students to enhance their knowledge and skills in various actual working environments. From the industrial training, the students will be able to gain the knowledge through hands-on observation and job execution as well as to improve soft skills such as communication, critical thinking, teamwork, work ethics, and leadership. The students are required to undergo industrial training for one semester attached to operations research with data science related organisation. Upon completion of the training, the students shall submit a report on the work done in the organisation to the faculty.Course Learning OutcomesAt the end of this course, students are able to:1. APPLY the knowledge that they have learned in the workplace. (C3)2. DEVELOP basic professional skills by experiencing a real working environment. (C5)3. PRODUCE Industrial Training report after the training is completed. (C5)References1. Sharifah Aishah Syed Ali, Fazilatulaili Ali and Ahmad Shafiq Abdul Rahman. (2020) Panduan Latihan Industri Sarjana Muda Penyelidikan Operasi dengan Sains Data. Jabatan Sains Pertahanan, FSTP, Universiti Pertahanan Nasional Malaysia2. Halip, M.H.M., Awang, N.F., Yahaya, Y.H., Khairuddin, M.A. & Ghani, S.A. (2011). Panduan Latihan Industri Sarjana Muda Sains Komputer. Kuala Lumpur: Jabatan Sains Komputer, Universiti Pertahanan Nasional Malaysia.
JABATAN SAINS DAN TEKNOLOGI MARITIM
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026185JABATAN SAINS DAN TEKNOLOGI MARITIMProfesor Prof. Dato' Ts. Dr. Ahmad Mujahid bin Ahmad Zaidi FAPM FCILTB.Eng. (Hons.)(Mechanical Engineering)(UTHM), Ph.D. (Mechanical Engineering)(The University of Manchester, UK)Prof. Dr. Nanthini Sridewi a/p Appan B.Sc. (Hons.)(Marine Science)(UMT), Ph.D. (Microbial Biotechnology)(USM)Prof. Ts. Dr. Mohamad Rosni bin Othman FCILTB.Sc. (Maritime Science)(UPM), M.Sc. (Maritime Management)(UMT), Ph.D. (Maritime Policy) (Newcastle University, UK)Profesor MadyaLt Kdr Prof. Madya Ts. Dr. Mohd Norsyarizad bin Razali TLDM (Bersara) CMILTB.Eng. (Hons.)(Electronics and Telecommunication)(UNIMAS), M.Sc. (Mathematics)(UTM), Ph.D. (Mathematics)(UTM)Pensyarah KananLt Kdr Ir. Ts. Hj. Mohd Najib bin Abdul Ghani Yolhamid TLDM (Bersara) CEng CMarEng CIMLT P.Eng. P.Tech MIMarEstB.Eng. (Hons.)(Electrics and Electronics)(UTM), M.Sc. (Physics)(UTM)Lt Kdr Ts. Dr. Mohd Azzeri bin Md Naiem TLDM (Bersara) CMILTB.Eng. (Mechanical)(UTM), M.Eng. (Marine Technology)(UTM), Ph.D. (Mechanical Engineering)(UTM)Lt Kdr Ir. Dr. Hardy Azmir bin Anuar TLDM (Bersara) PEPCB.Eng. (Hons.)(Computer Engineering)(Manchester Metropolitan University, UK), M.Eng. (Telecommunications)(UTM), Ph.D. (Robotics)(Ecole Centrale de Nantes, France)Kdr Dr. Hani Kalsom binti Hashim TLDM CMILTDip. Tech. Mgt. (UTM), B.Mgt. (Hons.) (USM), M.Mgt. (UNITAR), DBA (USM)Ts. Dr. Mohamad Abu Ubaidah Amir bin Abu Zarim MRINADip. Ship Eng Tech (Construction and Maintenance)(UniKL), B.Eng. (Hons.)(NA and ME) (Glasgow, UK), M.Sc. (Marine Eng.)(Strathclyde), Ph.D. Fluid mechanics (Ecole Centrale de Nantes, France)
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026186Kept Mohamad Zaid bin Sapii TLDMCategory A Hydrographic Survey Cert.(UTM), Dip. Strategic & Defence Studies (UM), BSc (Geology)(Flinders, Australia), M.Environment (UPM)Komander Ts. Hj Mohd Arif bin Ahmad TLDM (Bersara) Long (N) CoCMD CMILTDip. SP (INTAN), M.Sc. (Management)(UUM)Lt Kdr Dr. Nor Fyadzillah binti Mohd Taha TLDM (Bersara) CMILT UKB.Eng. (Hons.)(Electric and Electronic)(UTM), M.Sc. Engineering Business Management (UTM), MBA (Meiji University, Japan), Ph.D. in Logistics and Supply Chain (University of Hull, UK).Ts. Dr. Roshamida binti Abd. JamilB.Sc. (Hons.)(Maritime Tech.)(UPNM), M.Sc. (Maritime Operations)(LJMU, UK), Ph.D. in Fluid Mechanics (Ecole Centrale de Nantes, France)Ts. Suresh a/l ThanakodiB.Eng. (Electrical)(UTM), M.Eng. (Electrical Power)(UTM)PensyarahDr. Adenen Shuhada binti Abdul Aziz CMILTB.Sc. (Hons.)(Maritime Tech.)(UPNM), M.Sc. (Naval Architecture)(Southampton, UK), PhD (UPNM).Gs. Ainul Husna binti Abdul Rahman CMILTB.Sc. (Hons.)(Maritime Tech.)(UPNM), M.Sc. (Geospatial and Mapping Sc.)(Glasgow, UK)Lt Mohammad Hanif Dihani bin Mohd Zaidi TLDM (Bersara)B.Sc. (Hons.)(Maritime Tech.)(UPNM), M.Mar Tech (UPNM)Lt Ts Mohamad Azrin bin Abd Azis TLDM (Bersara)B.Sc. (Hons.)(Maritime Tech.)(UPNM), M.Mar Tech (UPNM)Gs. Dr. Nur Hazimah binti Nordin CMILTDip. (Geomatic Sc.)(UiTM), B.Sc. (Surveying Sc. & Geomatics)(UiTM), M.Sc. (Geographical Info. Sc.)(UiTM), Ph.D. (Computer Science)(UPNM)Norshaheeda binti Mohd Noor CMILTB.B.A. (International Business) (UPM), M.Sc. Logistics and Supply Chain Managemen(University of Hull, UK)Nurasyiqin binti Mohd Radzi CMILTB.B.A. (Hons.) (Transportation)(UiTM), M.B.A. (UMS)
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026187Gs. Siti Sarah binti Mohd Isnan CMILTB.Sc. (Hons.) (Maritime Tech.) (UPNM), M.Sc. (Geospatial and Mapping Sc.) (Glasgow, UK)Zulhilmi bin Muhammad Nasir CMILTB.B.A. (Hons.) (Logistics and Transport) (UUM), M.Sc. (Transport Planning) (UTM)Pensyarah Cuti BelajarLt Ts. Noh bin Zainal Abidin TLDM (Bersara)B.Eng.(Marine Tech)(UTM), Msc. (Hyrodynamic for Ocean Engineering)(Ecole Centrale de Nantes, France)
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026188OBJEKTIF DAN HASIL PEMBELAJARANPROGRAM IJAZAH SARJANA MUDA TEKNOLOGI MARITIM DENGAN KEPUJIAN (ZG39)Objektif Pembelajaran Program Programme Educational Objectives (PEO)Objektif Pembelajaran Program adalah pencapaian graduan yang dijangkakan dalam masa 3 – 5 tahun setelah bergraduat.Programme Educational Objectives (PEO) are what graduates are expected to attain within 3 – 5 years after graduation.Selepas 3 hingga 5 tahun bergraduat, pelajar Ijazah Sarjana Muda Teknologi Maritim dijangka:After 3 to 5 years of graduation, graduates of Bachelor in Maritime Technology, are expected to:i. Teknologis yang memiliki nilai peribadi dan etika yang positif.Technologist possess positive personal values and ethics.ii. Teknologis yang kompeten dalam bidang Teknologi Maritim.Competent technologist in the Maritime Technology fields. iii. Teknologis yang memiliki kepimpinan dan profesionalisme dalam bidang Teknologi Maritim.Technologist posses leadership and professionalism in Maritime Technology fields.Hasil Pembelajaran Program Programme Learning Outcomes (PLO)Setelah selesai mengikuti Sarjana Muda Teknologi Maritim, pelajar dijangka memperoleh:Upon completion of Bachelor in Maritime Technology, students are expected to:PLO 1Mengaplikasikan pengetahuan Sains dan Teknologi Maritim di kapal, pangkalan/terminal, pelabuhan, industri dan agensi maritim.Apply the knowledge of Maritime Science and Technology onboard ships, bases/terminals, ports and other maritime industries and agencies.PLO 2Mempamerkan kemahiran pemikiran kritikal dan penyelesaian masalah dalam Sains dan Teknologi Maritim.Demonstrate critical thinking and problem-solving skill in Maritime Science and Technology.PLO 3Mempamerkan kemahiran psikomotor, praktikal dan teknikal dalam bidang Sains dan Teknologi Maritim.Demonstrate psychomotor, practical and technical skills in Maritime Science and Technology.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026189PLO 4Mempamerkan kemahiran interpersonal dan kerja berpasukan dalam industri dan agensi.Demonstrate interpersonal and teamwork skills in industries and agencies.PLO 5Mempamerkankan komunikasi yang berkesan secara lisan dan bukan lisan melalui semua platform.Exhibit effective communication verbal and non-verbal via all platforms.PLO 6 Mengaplikasikan kemahiran numerasi dengan menggunakan teknologi digital.Apply numeracy skills using digital technology.PLO 7Mempamerkan kepimpinan secara efektif dan boleh dipertangunggjawabkan dalam pelbagai peringkat pengurusan untuk menjadi pemimpin intelektual yang berkarakter.Demonstrate leadership effectively and be accountable in various managerial capacities in order to be a responsible intellectual leaders of character.PLO 8Mempamerkan kemahiran insaniah untuk peningkatan kerjaya dan pembelajaran sepanjang hayat.Display personal skills for career enhancement and life-long learning.PLO 9 Mengaplikasikan kemahiran keusahawanan dan inovatif.Apply entrepreneurial and innovative skills.PLO 10Mempamerkan profesionalisme, nilai-nilai murni, sikap dan etika yang betul dalam persekitaran kerja. Demonstrate professionalism, good values, right attitudes and ethics in working environment.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026190STRUKTUR KURSUS DAN JUMLAH KREDIT KEPERLUAN PROGRAMIJAZAH SARJANA MUDA TEKNOLOGI MARITIM DENGAN KEPUJIAN (ZG39)JUMLAH KREDITJumlah keperluan kredit yang perlu dipenuhi untuk bergraduat adalah seperti mana jadual di bawah dan tempoh pengajian yang perlu diikuti adalah enam semester lazim dan dua semester pendek. Pecahan kursus yang perlu diambil adalah seperti berikut:KURSUS JAM KREDITKursus Universiti:i. Kursus Teras Universitiii. Kursus Elektif Universiti246Kursus Teras Program 66Kursus Elektif Program 10Projek Tahun Akhir 6Latihan Industri 12JUMLAH KREDIT UNTUK BERGRADUAT 120KURSUS TERAS PROGRAMKursus-kursus Teras Program adalah wajib diambil oleh semua pelajar Teknologi Maritim seperti berikut:KOD KURSUS NAMA KURSUS JAM KREDITTMM 3253 Seamanship and Ship Technology 3TMM 3263 Integrated Logistics Support 3TMM 3273 Ship Maintenance System 3TMM 3283 Human Resource Management 3TMM 3293 Management Theory and Practice 3TMT 3313 Technical Mathematics 3TMT 3323 Basic Electrical Technology 3TMT 3331 Seamanship and Ship Technology Lab 1TMT 3343 Basic Electronics 3
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026191KOD KURSUS NAMA KURSUS JAM KREDITTMT 3352 Nautical Law 2TMT 3361 Maritime Communication Lab 1TMT 3373 Maritime Communication 3TMT 3383 Navigation Science I 3TMT 3393 Astronomical Navigation 3TMT 3403 Maritime Law and Enforcement 3TMT 3412 Navigation Science Lab 2TMT 3423 Naval Architecture 3TMT 3433 Marine Technology System 3TMT 3483 Navigation Science II 3TMT 3493 Hydrography 3TMT 3503 Oceanography 3TMT 3513 Integrated Transportation System 3TMT 3523 Cargo Handling System 3TMT 3533 Digital Telecommunication System 3JUMLAH KREDIT 66KURSUS ELEKTIF PROGRAMBagi kursus Elektif Program, pelajar perlu memilih sebanyak 10 kredit sahaja. Kursus-kursus Elektif Program adalah seperti berikut:KOD KURSUS NAMA KURSUS JAM KREDITTMT 3723 Above Water Warfare Technology* 3TMT 3733 Marine Pollution**/*** 3TMT 3743 Marine Environmental Biotechnology**/*** 3TMT 3751 Introduction to Programming 1TMT 3763 Underwater Warfare Technology* 3
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026192TMT 3773 Weapon Electrical and Electronic System* 3TMT 3813 Maritime Economics**/*** 3PROJEK TAHUN AKHIRKOD KURSUS NAMA KURSUS JAM KREDITTMT 3462 Research Project I 2TMT 3474 Research Project II 4JUMLAH KREDIT 6LATIHAN INDUSTRIKOD KURSUS NAMA KURSUS JAM KREDITTMT 344C Industrial Training 12JUMLAH KREDIT 12Nota:* Diambil oleh Pegawai Kadet** Diambil oleh pelajar PALAPES*** Diambil oleh pelajar pelajar Awam
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026193STRUKTUR KURIKULUMPROGRAM IJAZAH SARJANA MUDA TEKNOLOGI MARITIM DENGAN KEPUJIAN (ZG39)TAHUN PERTAMASEMESTER 1 SEMESTER 2KOD KURSUS NAMA KURSUS KREDIT KOD KURSUS NAMA KURSUS KREDITDUS3042 Military History and Leadership 2 MPU3132 Appreciation of Ethics and Civilizations 2MPU3142 Philosophy and Currents Issues 2 MPU3212 Basic Entrepreneurship 2MPU3412/MPU3422/ MPU3432Human Movement Science / Community Service / Nationhood in World Politics2 LLE3032 Al-Ghazali’s Dialogue: English Communication 2LLE3012 English for Academic Writing 2 LLF3XX1 Foreign Language II 1LLF3XX1 Foreign Language I 1 TMT3343 Basic Electronics 3TMM3253 Seamanship and Ship Technology 3 TMT3352 Nautical Law 2TMT3313 Technical Mathematics 3 TMT3361 Maritime Communication Lab 1TMT3323 Basic Electrical Technology 3 TMT3373 Maritime Communication 3TMT3331 Seamanship and Ship Technology Lab 1 TMT3533 Digital Telecommunication System 3PLS3111/ QKA3111PALAPES 1/ Kesatria Al-Fateh 1 1ALK3112/ PLS3121/ QKA3121Latihan Ketenteraan Umum / PALAPES 2 / Kesatria Al-Fateh 22 / 1JUMLAH KREDIT 20 JUMLAH KREDIT 21/ 20SEMESTER PENDEKKOD KURSUS NAMA KURSUS KREDITTMM 3283 Human Resource Management 3TMM 3293 Management Theory and Practice 3JUMLAH KREDIT 6
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026194TAHUN KEDUASEMESTER 3 SEMESTER 4KOD KURSUS NAMA KURSUS KREDIT KOD KURSUS NAMA KURSUS KREDITDUS3022 Introduction to Strategic Studies 2MPU3322 /MPU3332/ MPU3342Blue Ocean Strategy and Total Defence / Fiqh Keutamaan/ Integrity and Anti- Corruption2TMT3383 Navigation Science I 3 TMT3462 Research Project I 2TMT3403 Maritime Law and Enforcement 3 TMT3423 Naval Architecture 3TMT3412 Navigation Science Lab 2 TMT3493 Hydrography 3TMT3433 Marine Technology System 3 TMT3513 Integrated Transportation System 3TMT3751Elective I:Introduction to Programming1 TMT37X3Elective III:(TMT 3763 – Under Water Warfare Technology* / TMT 3733 - Marine Pollution**)3TMT37X3Elective II:(TMT 3723 – Above Water Warfare Technology* / TMT 3743 - Marine Environmental Biotechnology**)3 TMT3XX3Elective IV: (TMT 3773 - Weapon Electrical and Electronic System* / TMT 3813 - Maritime Economics**)3ALK3122 / PLS3131 / QKA3132Latihan Ketenteraan Umum/ PALAPES 3 / Kesatria Al-Fateh 32 / 1QKS3172/ PLS3141 / QXX YYY2Tempur Tanpa Senjata / PALAPES 4 / Ko-Kurikulum2 / 1JUMLAH KREDIT 19 / 18 JUMLAH KREDIT 21 / 20SEMESTER PENDEKKOD KURSUS NAMA KURSUS KREDITTMM 3273 Ship Maintenance System 3TMT 3503 Oceanography 3JUMLAH KREDIT 6
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026195TAHUN KETIGASEMESTER 5 SEMESTER 6KOD KURSUS NAMA KURSUS KREDIT KOD KURSUS NAMA KURSUS KREDITTMT 3474 Research Project II 4 TMT 344C Industrial Training 12TMM 3263 Integrated Logistics Support 3TMT 3393 Astronomical Navigation 3TMT 3483 Navigation Science II 3TMT 3803 Cargo Handling System 3PLS 3151 PALAPES 5 1PLS 3161 PALAPES 6 1JUMLAH KREDIT 16 / 18 JUMLAH KREDIT 12Nota:* Diambil oleh Pegawai Kadet** Diambil oleh pelajar PALAPES dan Awam
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026196SINOPSIS KURSUS TERAS PROGRAMSARJANA MUDA TEKNOLOGI MARITIM DENGAN KEPUJIAN (ZG39)Course Code: TMM 3253Course Name: KEPELAUTAN DAN TEKNOLOGI KAPAL SEAMANSHIP AND SHIP TECHNOLOGYCredit Hour: 3Pre-requisite: NoneSynopsisThis course is to provide students with the fundamental knowledge of seamanship, ship technology and awareness on the safety of life at sea. The goal of this course is to deliver knowledge and understanding of seamanship, advancement in ship technology, technology on navigation safety, nuclear, biological, chemical defence and damage control, naval training technology, ship stability, disaster control, helmsman ship and new technology in survival at sea. Upon completion of this course, students should be able to comprehend the knowledge of seamanship and ship technology and their application onboard ship.Course Learning OutcomesAt the end of this course, students are able to:1. Identify the essential knowledge of seamanship and ship technology.2. Explain the various types of seamanship evolutions onboard RMN ships.3. Differentiate the seamanship organisation and maintenance management system.4. Compose essay and create presentation on seamanship and ship technology-related topics.5. Integrate the usage of ship’s safety equipment and gears in emergency and urgency situations such as fire, flooding and collision.References1. Dewan Bahasa dan Pustaka (1995). Manual Admiralti Ilmu Kepelautan. Jilid I. Kuala Lumpur: Dewan Bahasa dan Pustaka.2. Mack, W. (1991). Naval Officer Guide. Annapolis, Maryland: Naval Institute Press.3. Royal Navy (1995). Admiralty Manual of Seamanship BR 67. London: HMSO.4. Royal Navy (1995). Guide to Ship Firefighting BR 4007. London: HMSO.5. Sharpe, R.(2010). Jane’s Fighting Ship. London: Butler & Taner.6. Zulkifly Mat Radzi (2016). Modul Psikomotor dan Afektif Menggunakan Teknologi Simulator.Kuala Lumpur: Universiti Pertahanan Nasional Malaysia.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026197Course Code: TMM 3263Course Name: BANTUAN SISTEM LOGISTIK BERSEPADUINTEGRATED LOGISTICS SUPPORTCredit Hour: 3Pre-requisite: NoneCourse SynopsisThis course provides students with the knowledge on Integrated Logistics Support (ILS) and its application which covers materials life cycles, elements of ILS, project management principles, ship logistics, general ship supply, funds and budget. This course will cover the concepts of logistics support with respect to ship repairs and maintenance of equipment and/or systems onboard ships.Course Learning OutcomesAt the end of this course, students are able to: 1. Describe the concepts of supply and support in relation to logistics.2. Relate the integrated logistics support concepts in aspects of ship supply and maintenance.3. Apply Logistic Support Analysis with regard to the equipment/systems onboard ships.4. Analyse the Reliability, Availability and Maintainability (RAM), and System Effectiveness onboard ships.References1. Blanchard, B.S. & Fabrycky, W.J. (2006). System Engineering and Analysis. London: Pearson Prentice Hall.2. Jones, J.V. (2010). Engineering Design: Reliability, Maintainability and Testability. San Francisco: Logistics Management Associates.3. Jones, J.V. (2010). Integrated Logistics Support Handbook. Third Edition. New York: McGrawHill.4. Jones, J.V. (2006). Supportability Engineering Handbook: Implementation, Measurement and Management. New York: McGraw-Hill.5. Kumar, D. (2006). Reliability, Maintenance and Logistics Support: A Life Cycle Approach. London: Springer.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026198Course Code: TMM 3273Course Name: SISTEM SENGGARAAN KAPAL SHIP MAINTENANCE SYSTEM Credit Hour: 3Pre-requisite: NoneCourse Synopsis This course introduces the essential knowledge of maintenance practice and refit procedures for students. The subject covers on general principles of maintenance, reliability-centred maintenance, ship maintenance system and ship refit. Upon completion of this course, the students should be able to plan and execute the different levels of maintenance onboard ships. Course Learning Outcomes At the end of this course, students are able to: 1. Comprehend the general principles of maintenance. 2. Demonstrate the concept of different levels of maintenance onboard ships.3. Predict the maintenance requirements onboard ship asset management. References 1. Duffuaa, Salih, Raouf, A. (2015). Planning and Control of Maintenance Systems, Switzerland: Springer International Publishing. 2. U. Kumar, A. Ahmadi, AK. Verma, P. Varde. (2015). Current Trends in Reliability, Availability, Maintainability and Safety, Switzerland: Springer International Publishing.3. Caridis P.A (2009). Inspection, Repair and Maintenance of Ship Structures, 2nd Ed. London:Witherby & Co Ltd. 4. Royal Malaysian Navy. (2002). Panduan Pengurusan Senggaraan Berjadual Kapal-Kapal Di Limbungan BRL 1910. Lumut: RMN. 5. Royal Malaysian Navy. (1985). RMN Maintenance System BRL 1985. Lumut: RMN.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026199Course Code: TMM 3283Course Name: PENGURUSAN SUMBER MANUSIAHUMAN RESOURCE MANAGEMENT Credit Hour: 3Pre-requisite: NoneCourse SynopsisThis course is to provide an understanding and knowledge on Human Resource Management (HRM) including aspects on divisional matters pertaining to its application in an organisation. Among the topics discussed are HRM planning, training and promotion policy, employer-employee relation, job analysis and application of human resource aspects in an organisation. Students will be encouraged to develop critical thinking skills, teamwork and communication skills through group assignments and presentations. Course Learning OutcomesAt the end of this course, students are able to: 1. Explain the concepts of human resource management for their application in an organisation.2. Appraise the personnel performance in an organisation. 3. Develop leadership, teamwork, interpersonal skills through group discussions and presentations. References1. Aminuddin, M. (2017). Human Resource Management: Principles and Practices. Fourth edition. Kuala Lumpur: Oxford University Press.2. Noe, R.A. (2012). Fundamentals of Human Resource Management. New York: McGraw-Hill. 3. Robbins, S.P. (2011). Management. Eleventh Edition. New Jersey: Prentice Hall.4. Royal Malaysian Navy. MBR 1066, RMN Divisional Officers Guide. Lumut: RMN.5. Scott, S. & Bohlander, G. (2010). Principles of Human Resource Management. Fifteenth edition. Ohio: South-Western Cengage Learning.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026200Course Code: TMM 3293Course Name: TEORI DAN AMALAN PENGURUSANMANAGEMENT THEORY AND PRACTICE Credit Hour: 3Pre-requisite: NoneCourse SynopsisThis course provides knowledge and understanding on the principles and practices of management. The syllabus includes aspects on planning, organising leading and controlling an organisation. Among the topics covered are decision-making process, the traits on leadership, teamwork, motivation and entrepreneurship. Students will be exposed to the generic management skills required for the job of an Executive Officer. Students will be encouraged to develop critical thinking skills and teamwork and communication skills through group assignments and presentations.Course Learning OutcomesAt the end of this course, students are able to: 1. Practise the principles of management in their future job as an Executive Officer. 2. Demonstrate the ability in planning and organising of activities in an organisation. 3. Develop leadership, teamwork, interpersonal skills through group discussions and presentations. References1. Baron, J.N. & Kreps, D.M. (1999). Strategic Human Resources: Frameworks for General Managers. New York: John Wiley & Sons, Inc. 2. Noe, R.A. (2012). Fundamentals of Human Resource Management. New York: McGraw-Hill. 3. Robbins, S.P. (2011). Management. Eleventh Edition. New Jersey: Prentice Hall.4. Royal Malaysian Navy. MBR 1066, RMN Divisional Officers Guide. Lumut: RMN5. Scott, S. & Bohlander, G. (2010). Principles of Human Resource Management. Ohio: SouthWestern Cengage Learning.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026201Course Code: TMT 3313Course Name: MATEMATIK TEKNIKAL TECHNICAL MATHEMATICS Credit Hour: 3Pre-requisite: NoneCourse SynopsisThis course provides foundational knowledge in solving differential equations relevant to technical fields. It covers first and second order ordinary differential equations, including their principles, concepts and analytical solution techniques. Students will also learn numerical methods such as Euler’s and Runge-Kutta methods for solving differential equations iteratively. Additionally, the course introduces Laplace Transforms, including the use of transform tables and techniques for handling partial fractions with linear, quadratic and trinomial factors. Upon completion of this course, students should be able to solve differential equations using analytical, numerical and Laplace Transform methods effectively.Course Learning OutcomesAt the end of this course, students are able to:1. Comprehend the basic concepts and classification of ordinary differential equations.2. Solve ordinary differential equation of first and second order using various solving methods and techniques.3. Apply the numerical methods and Laplace Transform to solve linear differential equations.References1. Kuhfittig, P. (2012). Technical Calculus with Analytic Geometry. Fifth Edition. New Jersey: Thomson. 2. Calter, P.A. & Calter, M.A. (2011). Technical Mathematics with Calculus. Sixth Edition. New York: John Wiley & Sons.3. Ewan, D., Gary, J.S & Trefzger, J.E. (2005). Technical Mathematics with Calculus. Second Edition. New Jersey: Prentice Hall.4. Allyn, Richard (2017), Basic Technical Mathematics, 11th ed., United States: Pearson Education5. K. A. Stroud , Dexter J. Booth (2013), Engineering Mathematics, 7th ed., UK: Macmillan
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026202Course Code: TMT 3323Course Name: ASAS TEKNOLOGI ELEKTRIKBASIC ELECTRICAL TECHNOLOGY Credit Hour: 3Pre-requisite: NoneCourse SynopsisThis course will prepare students with the fundamental knowledge on electrical technology that can be applied when serving onboard ship and bases. The students should be able to analyse and calculate the voltage and current in basic electrical circuits using Ohm’s Law and Kirchhoff’s Law. The students should be able to analyse basic circuit consisting of Resistor, Inductor and Capacitor (RLC). The students should also acquire knowledge on principles of motors, alternators and transformers.Course Learning OutcomesAt the end of this course, students are able to:1. Apply the basic concepts of electrical circuits and electric machines.2. Conduct unsupervised simulation on simple electric circuits.3. Explain the concept of electrical in the real world or for military applications.References1. Bird, J. (2010). Electrical and Electronic Principles and Technology. Fourth Edition. Oxford: Newnes.2. Cook, N.P. (1997). Practical Electricity. Harlow: Prentice Hall.3. Hughes, E. (2002). Hughes Electrical Technology. Seventh Edition. Harlow: Prentice Hall.4. National Joint Apprenticeship and Training Committee. (2008). DC Theory. Second Edition. New York: Delmar Cengage Learning.5. Rizzoni, G. & Hartley, T.T. (2007). Principle and Application of Electrical Engineering. Fifth Edition. Boston: McGraw-Hill.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026203Course Code: TMT 3331Course Name: MAKMAL KEPELAUTAN DAN TEKNOLOGI KAPALSEAMANSHIP AND SHIP TECHNOLOGY LAB Credit Hour: 1Pre-requisite: NoneCourse SynopsisThis course is to familiarise the students with the seamanship and ship technology skills as required when performing the duties of an Officer of the Watch (OOW) at sea and in harbour and to provide the students with the competency on seamanship training to enable them to undertake the job as an Officer of the Watch onboard a ship.Course Learning OutcomesAt the end of this course, students are able to:1. Adapt the use of steering wheel, throttle, compass and other navigation equipment fitted at the Ship Bridge Simulator.2. Initiate the recovery of Man Over Board (MOB) procedure using Williamson Turn or Anderson Turn.3. Display conning and steering the ship as directed by the OOW.4. Compose report as a lookout on duty to the OOW.References1. Dewan Bahasa dan Pustaka. (1995). Manual Admiralti Ilmu Kepelautan. Jilid I. Kuala Lumpur: Penerbitan Dewan Bahasa dan Pustaka.2. Mack, W. (1991). Naval Officer Guide. Annapolis Maryland: Naval Institute Press.3. Royal Navy. (1995) Admiralty Manual of Seamanship BR 67. London: HMSO.4. Royal Navy. (1995). Guide to Ship Firefighting BR 4007. London: HMSO. 5. Sharpe, R. (2010). Jane’s Fighting Ship. London: Butler & Taner.6. Zulkifly Mat Radzi (2016). Modul Psikomotor dan Afektif Menggunakan Teknologi Simulator.Kuala Lumpur: Universiti Pertahanan Nasional Malaysia.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026204Course Code: TMT 3343Course Name: ASAS ELEKTRONIKBASIC ELECTRONICS Credit Hour: 3Pre-requisite: NoneCourse SynopsisThis course will prepare students with the fundamental knowledge on basic electronics components. The students should be able to analyse and solve problems on circuits of diode, transistor, operational amplifier and logic gates.Course Learning OutcomesAt the end of this course, students are able to:1. Apply the basic concepts of analogue and digital circuits.2. Conduct unsupervised simulation on simple electronic circuits.3. Explain the concept of analogue or digital circuits in the real world or for military applications.References1. Boylestad, R.L. & Nashelsky, L. (2014). Electronic Devices and Circuit Theory. Eleventh Edition. Essex: Pearson Education Limited.2. Floyd, T.L. (2012). Electronic Devices. Ninth Edition. New Jersey: Pearson Education.3. Floyd, T.L. (2008). Digital Fundamentals. Tenth Edition. New Jersey: Pearson Education.4. LaLond, D. & Ross, J. (1994). Principles of Electronic Devices and Circuits. New York: Delmar Publishers.5. Stephen, C. (2000). Introduction to Electronics DC/AC Circuits. New Jersey: Prentice Hall.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026205Course Code: TMT 3352Course Name: UNDANG-UNDANG NAUTIKANAUTICAL LAW Credit Hour: 2Pre-requisite: NoneCourse SynopsisTo provide students with the knowledge on the International Regulations for Preventing Collisions at Sea 1972, conducting of vessel in any condition of visibility and enable them to perform the job of the Officer of the Watch/Deck (OOW/OOD) onboard ships. Upon completion of this course, students should have the ability to apply the rules and regulations while navigating a vessel at sea, identify the various visual displays used by vessels such as shapes, lights and sound signals, assess the risks of collision and apply the appropriate rules and regulations for preventing collisions at sea. The students also should be able to apply their knowledge in bridge watch keeping duty at sea and respond appropriately in a close quarter situation as an Officer of the Watch.Course Learning OutcomesAt the end of this course, students are able to:1. Apply various visual displays and sound signals used by vessels for navigational safety. 2. Analyse and provide solutions to problems and challenges in accordance with the rules and regulations for preventing collisions at sea. 3. Develop competency of applying the rules in various situations at sea in the Ship Handling Simulator. References1. IMO. (2003). COLREG International Regulations for Preventing Collision at Sea. London: International Maritime Organisation. 2. U.S. Department of Homeland Security. (2007). Navigation Rules for International and Inland Waters. Washington: Naval Institute Press.3. Bristol Tutor Group. (2003). A Seaman's Guide to the Rule of the Road. Bristol: BTG.4. Morehouse, J.M. (2010). Navigation Rules International-Inland. United States Coast Guard edition. Washington D.C.:Paradise Cay Publication.5. Farwell's Rules of the Nautical Road. Annapolis Maryland: Naval Institute Press.6. Zulkifly Mat Radzi (2016). Modul Psikomotor dan Afektif Menggunakan Teknologi Simulator. Kuala Lumpur: Universiti Pertahanan Nasional Malaysia.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026206Course Code: TMT 3361Course Name: MAKMAL KOMUNIKASI MARITIMMARITIME COMMUNICATIONS LABORATORYCredit Hour: 1Pre-requisite: NoneCourse SynopsisThis course aims to practise the maritime communication procedures and apply established communication onboard Officer in Tactical Command (OTC) ship and three other ships. Students are able to learn about communication check, time check, repetition, errors and clarification. They are also able to understand the procedure of sending and receiving time signal onboard a ship, e.g. entering and leaving harbour, jackstay transfer, towing, visual and blind pilotage. Procedure of sending and receiving signal using delay executive method onboard a ship, e.g. during tactical manoeuvre. Procedure of sending and receiving signal using immediate executive method during tactical manoeuvre. Message Writing. Drafting of signal message for the transmission. Tactical Communication. Fleet manoeuvre for basic formation 1 to formation 12. Fleet manoeuvre for Turn and Corpen. Fleet manoeuvre for advance formation, e.g. Corpen Sierra, Formation Oscar, Formation Yankee and Corpen Delta.Course Learning OutcomesAt the end of this course, students are able to:1. Practise the maritime communication procedure during the fleet manoeuvring exercise, entering and leaving harbour, replenishment at sea and formation anchorage.2. Demonstrate competency in radio and tactical communications at Ship Navigation Simulator.3. Perform the role as an Officer of the Watch during fleet manoeuvring exercise.References1. ACP 125 (F) Communication Instructions Radiotelephone Procedures (2001). Brussels: NATO Publication.2. Allied Tactical Publication I(A) Vol. I and II (1999). Brussels: NATO Publication.3. Malaysian Communication Publication Vol. I and II (1999). Kuala Lumpur: RMN Publication.4. Dewan Bahasa dan Pustaka (1995). Manual Admiralti Ilmu Kepelautan. Jilid I. Kuala Lumpur: Dewan Bahasa dan Pustaka.5. RMNCP 251 Signal Message Writing Instruction (2001). Kuala Lumpur: RMN Publication.6. Zulkifly Mat Radzi (2016). Modul Psikomotor dan Afektif Menggunakan Teknologi Simulator. Kuala Lumpur: Universiti Pertahanan Nasional Malaysia.
Buku Panduan Akademik, FSTP Sesi Akademik 2025/2026207Course Code: TMT 3373Course Name: KOMUNIKASI MARITIMMARITIME COMMUNICATIONSCredit Hour: 3Pre-requisite: NoneCourse SynopsisThe aim of this course is to provide students with the knowledge of Maritime Communications and apply the knowledge onboard ships. The course is to expose students to the advance and fundamental methods of communication, shipboard communication in different frequencies of HF, VHF and UHF, long range radio communication, shore to shore, ship to shore, shore to ship, broadcast, communication network, communication plan, cryptography, message handling, communication security and tactical manoeuvre. Upon completion of this course, students should be able to comprehend the latest development of technologies on maritime communication such as satellite communication, underwater communication and latest line of sight communication between ships, aircraft and submarines.Course Learning OutcomesAt the end of this course, students are able to:1. Describe the fundamental and advance technologies in maritime communications.2. Apply the knowledge of maritime communications onboard ships and maritime agencies.3. Analyse and provide solution to problems and issues in maritime communications.References1. Dewan Bahasa dan Pustaka. (1995). Manual Admiralti Ilmu Kepelautan. Jilid I. Kuala Lumpur: Dewan Bahasa dan Pustaka.2. National Defence University of Malaysia. (2010). Maritime Communications Lecture Notes.Kuala Lumpur: NDUM Unpublished.3. Kim, J.C. & Muehldorf, E.I. (2005) Naval Shipboard Communication System. New Jersey: Prentice Hall.4. Royal Malaysian Navy. (1999). Malaysian Communication Publication (Vol. 1-2). Kuala Lumpur: RMN Publication.5. Royal Malaysian Navy. (1999). RMN Tactical Publication (Vol. 1-2). Kuala Lumpur: RMN Publication.6. Zulkifly Mat Radzi (2016). Modul Psikomotor dan Afektif Menggunakan Teknologi Simulator.Kuala Lumpur: Universiti Pertahanan Nasional Malaysia.