Abstract Book CMCS 2021

COMPUTER AND MATHEMATICAL SCIENCES CONFERENCE 2021
(CMSC 2021)

CONFERENCE THEME
“DRIVING THE DEMAND OF ARTIFICIAL INTELLIGENCE, DATA SCIENCE AND

DIGITAL TECHNOLOGY TOWARDS RESEARCH EXCELLENCE”

CONFERENCE DATE
25 NOVEMBER 2021

CONFERENCE PLATFORM
GOOGLE MEET

ORGANIZED BY
FACULTY OF COMPUTER & MATHEMATICAL SCIENCES

UNIVERSITI TEKNOLOGI MARA, SABAH BRANCH
KOTA KINABALU CAMPUS

Table of contents

Preamble 1
2
Organizing Committee 3
4
Programme Tentative 5
6
List of Abstract 7

CMSC 01 - Competition-Based Learning Model: A Case in UiTM Sabah 8
Branch
9
CMSC 02 - Exploring the Robust Changes in Age-Pattern of Fertility in
Malaysia: An Approach of Functional Data Analysis 10

CMSC 03 - Fekete-Szegö of Certain Bi-univalent Function defined by
Quasi-subordination

CMSC 04 – Risks of Alzheimer’s Disease among Primary Open Angle
Glaucoma Patients Based on MTA and PCA Scoring in Brain Using
T1-MPRAGE

CMSC 05 - HoH16StepsGL: A Clear-Cut Interactive Hypothesis Testing
Notes

CMSC 06 – Application of Fuzzy TOPSIS Method for Selecting Part-Time
Lecturers: A Case Study of Faculty of Computer & Mathematical Sciences
UiTM Sabah Branch

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preamble

CMSC 2021 was the third conference organized by the Faculty of Computer and
Mathematical Sciences, UiTM Sabah. This was the first time that the conference was
conducted virtually due to the current pandemic situation. Nevertheless, the number of
participations to CMSC 2021 has been overwhelming. As it was for the previous
conferences, the main aim of CMSC 2021 is to provide a venue where academics and
researchers can discuss and exchange views on their latest findings in research and
innovation projects. In line with current issues, the conference has chosen the theme
“Driving Artificial Intelligence, Data Science and Digital Technology towards Research
Excellence”. The scope covers, but not limited to, digital teaching & learning, data
modelling & simulation, big data analytics, machine learning and complex data analysis.
The theme is relevant with the current Covid-19 pandemic situation that has affected many
aspects of human life. For instance, the education system has undergone a drastic
technological shift. Such change has resulted in an indisputable rise of e-learning
approaches that has created a need for the teaching and learning process to be conducted
remotely hence requiring high digitalization capabilities. Despite the challenges, the
integration of high-ends technologies into the education system has opens up opportunities
to create an attractive and effective educational environment that could stimulate students'
interest and engagement.

In this day and age, artificial intelligence technology (AI) and big data are the enablers for
the internet of things (IOT). Going forward, these new technologies are expected to bring
about major changes in the way things work in various fields where the field of education
is no exception. Accordingly, AI is expected to contribute to new knowledge through the
development of new digital education models and hence encourages greater data access for
researchers. As there has been a tremendous increase in the scope of data in recent years,
the data science is expected to play an important role in high-end analysis and decision
making. With the development, new models in digital teaching and learning can be
developed through research projects which aim is to produce innovative and globally
competitive students that are equipped with relevant skills to meet the nation’s aspiration.

To conclude, on behalf of the Faculty of Computer and Mathematical Sciences, UiTM
Sabah, the conference committees would like to express gratitude to the Academic Affairs
Division, UiTM Sabah and everyone who have supported CMSC 2021. Our heartfelt thank
you & appreciation also goes to all who have shown interest and made contributions to the
success of the conference. We sincerely hope that CMSC will continue to be a forum for
future academic discourse to promote more development in scientific research.

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Organizing committee

CONFERENCE ADVISOR 2
Dr Firdausi Suffian

CONFERENCE PRESIDENT
Dr Khairul Bin Anwar

CONFERENCE COORDINATOR
Hazlenah Binti Hanafiah

SECRETARY
Norfazilah Matmali

TREASURER
Hasmiah Binti Bahari

TECHNICAL COMMITTEE
Dr Rashidah Binti Omar
Ung Ling Ling
Nasrah Bin Naharu
Fatihah Anas Muhiddin
Saiful Nizam Bin Amran
Roseline Michael
Nowyannie Willie D. Tamsin
Jais Bin Abdul Fatah
Marsus Bin Jabar
Norah Tuah
Mazalan Bin Sarahintu
Tammie Christy Saibin
Janvin Janteng
Azmi Samad

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Programme tentative

TIME EVENT

8.30 AM Arrival of Participants & Registration in Google Meet
9.00 AM National Anthem Negaraku & Sabah Tanah Airku Song
Doa Recitation
9.30 AM Welcoming Address by Dr Khairul Anwar, Coordinator, Faculty of
Computer & Mathematical Sciences
Inaugural Speech by Honourable Dr Firdausi Suffian, Deputy Rector,
Academic Affairs
Multimedia Presentation
Wawasan Setia Warga UiTM Song
Photo Session

SESSION 1 PRESENTATION

11.00 AM – 1.00 PM Presenter: Tammie Christy Saibin
Competition-Based Learning Model: A Case in UiTM Sabah Branch

Presenter: Hazlenah Hanafiah

Exploring the Robust Changes in Age-Pattern of Fertility in
Malaysia: An Approach of Functional Data Analysis

1.00 PM – 2.00 PM Presenter: Dr Rashidah Omar
2.00 PM – 4.00 PM Fekete-Szegö of Certain Bi-univalent Function defined by Quasi-
subordination

LUNCH
SESSION 2 PRESENTATION

Presenter: Adelina Ebun
Risks of Alzheimer’s Disease among Primary Open Angle Glaucoma
Patients Based on MTA and PCA Scoring in Brain Using T1-
MPRAGE

Presenter: Norah Tuah
HoH16StepsGL: A Clear-Cut Interactive Hypothesis Testing Notes

Presenter: Mazalan Sarahitu
Application of Fuzzy TOPSIS Method for Selecting Part-Time
Lecturers: A Case Study of Faculty of Computer & Mathematical
Sciences UiTM Sabah Branch

4.00 PM Certificate Presentation Ceremony
4.30 PM End of Conference

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List of abstract

NO TITTLE OF ABSTRACT AUTHOR(S)

CMSC Competition-Based Learning Model: A Case in UiTM Tammie Christy Saibin,
01
Sabah Branch Janvin Janteng, Norfazillah

Matmati

CMSC Exploring the Robust Changes in Age-Pattern of Malay Hazlenah Hanafiah, Adelina

02 Fertility: An Approach of Functional Data Analysis Ebun, Siti Aishah Hanawi

CMSC Fekete-Szeg ̈ of Certain Bi-univalent Function Dr Rashidah Omar,
03 defined by Quasi-subordination
Norfazillah Matmali,

Munirah Rossdy

CMSC Risks of Alzheimer’s Disease among Primary Open Angle Adelina Ebun, Hazlenah
04 Glaucoma Patients Based on MTA and PCA Scoring in
Brain Using T1-MPRAGE Hanafiah, Khairul Anwar,

Mohammad Hanafiah

Kreah

CMSC HoH16StepsGL: A Clear-Cut Interactive Hypothesis Norah Tuah, Roseline
05 Testing Notes
Michael, Hazlenah

Hanafiah

CMSC Application of Fuzzy TOPSIS Method for Selecting Mazalan Sarahitu, Munirah
06 Part-time Lecturers: A Case Study of Faculty of Rossdy,
Computer & Mathematical Sciences UiTM Sabah Dr Zamali Tarmudi
Branch

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CMSC 01

Competition-Based Learning Model: A Case in UiTM
Sabah Branch

Tammie Christy Saibin1, a), Janvin Janteng1,b), Norfazillah Matmali1,c)

1Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Sabah Branch,
Kota Kinabalu Campus, Locked Bag 71, 88997 Kota Kinabalu, Sabah

a)Corresponding author: [email protected]
b)[email protected]

c) [email protected]

Abstract. Competition motivates students to seek new knowledge and enhance their skills to
succeed against their competitors. Competition-based learning (CBL) focuses not only on
reward or incentives but also on learning as an outcome. The CBL model used in this paper
was developed by Issa, Hussain, and Al-Bahadili (2014). This model combines Project-Based
Learning (PBL) and competition. This model can also be used in a networked environment
where the latest technologies in computers and networks were in place. A networked
environment supports social interactions where learning can be anywhere and anytime. This
new model claims to be an alternative solution to students’ problems with traditional practices:
such as lack of motivation, low self-esteem, the insufficient practice of real-world problems,
and inadequate teamwork practices. This paper presents the implementation of the competition
using the components of the proposed CBL model. Finally, their presentation grading and
analysis from the feedback obtained from the students. The result from the survey and
comparing the overall subject achievements with and without CBL provides insight that CBL
motivates students and helps them increase their academic performance.

Keywords. competition-based learning, teaching and learning strategies, mathematics,
competitions

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CMSC 02

Exploring the Robust Changes in Age-Pattern of Fertility
in Malaysia: An Approach of Functional Data Analysis

Hazlenah Hanafiah1,a), Adelina Ebun2,b), Siti Aishah Hanawi3,c),

1Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Sabah Branch,
Kota Kinabalu Campus, Locked Bag 71, 88997 Kota Kinabalu, Sabah

2Faculty of Accountancy, Universiti Teknologi MARA Sabah Branch, Kota Kinabalu Campus,
Locked Bag 71, 88997 Kota Kinabalu, Sabah

3SOFTAM, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia,
43600 Bangi, Selangor

a)Corresponding author: [email protected]
b)[email protected]
c) [email protected]

Abstract. Population growth plays an important role and contributes to a rapid economic development.
Accordingly, the fertility level is prominent in determining a stable population growth. Despite the vast
studies, the classical method that focuses on point-based data have commonly been used to understand
fertility issues. Additionally, there has been a dearth of studies that examine the age-related factors in
Malaysia. Arguably, the disaggregation of fertility rates based on mother’s age is paramount as this
indicates a change in the timing of childbearing. By using the Malays, the dominant ethnic group in
Peninsular Malaysia (69.6%), this study identifies the robust changes in the fertility curve based on the
age-group of mothers. The data covers age-specific fertility rates over a period of 18 years (2001 to
2018). In doing so, the point-based data is transformed into a function using the B-spline method. Hence,
the functional data allows the generated curve to be smoothed naturally to reduce the observation error.
Thereafter, a Functional Box Plot Analysis was applied to provide a generalization of the concepts of
median, percentile and extreme values. This enables the outcomes to be portrayed spatially through the
picture of the curves. Based on the findings, the level of Malays fertility showed a continuous declining
pattern for all age-groups of mothers and an ostensible trend of later childbearing.

Keywords. Age-Specific-Fertility Rate (ASFR), Functional Data Analysis (FDA), Robust, B-Spline

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CMSC 03

Fekete-Szeg ̈ of Certain Bi-univalent Function defined by
Quasi-subordination

Rashidah Omar1, a) Norfazillah Matmali1, b) And Munirah Rossdy 1, c)

1 Facultyi of Computer and Mathematical Sciences, Universiti Teknologi MARA Sabah Branch,
Kota Kinabalu Campus, Locked Bag 71, 88997 Kota Kinabalu, Sabah

a)Corresponding author: [email protected]
b)[email protected]
c) [email protected]

Abstract. Geometric functions theory is the oldest area in mathematics. This theory is widely applied
in physics, computer, engineering etc. It is related to geometric properties of analytic functions which
is concerned with a distance, shape and size. Besides that, it is included a determinant properties f a
square matrix. For example, determinant of 2x2 matrix is given as | | = − . Determinant can
be used in solving a system of equations. More generally, in 1933, Fekete-Szegö obtained the
properties of | 3 − 22| for coefficients of Maclaurin series. In this paper, Fekete-Szegö inequality is
determined based on bi-univalent function using quasi-subordination concept. Some equations are
derived from quasi-subordination method. Then, by comparing the coefficients of these equations, the
second and third coefficients are obtained. Carathé odory Lemma is applied in getting these coefficients
and Fekete-Szegö inequality. Hence, the properties of Fekete-Szegö for certain bi-univalent function
is obtained.

Keywords. Fekete-Szegö inequality; bi-univalent functions; quasi-subordination, coefficients, analytic
functions.

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CMSC 04

Risks of Alzheimer’s Disease among Primary Open Angle
Glaucoma Patients Based on MTA and PCA Scoring in

Brain Using T1-MPRAGE

Adelina Ebun1, a), Hazlenah Hanafiah2,b), Khairul Anwar 2,c), Mohammad
Hanafiah Kreah3,d)

1Faculty of Accountancy, Universiti Teknologi MARA Sabah Branch, Kota Kinabalu Campus,
Locked Bag 71, 88997 Kota Kinabalu, Sabah

2Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Sabah Branch,
Kota Kinabalu Campus, Locked Bag 71, 88997 Kota Kinabalu, Sabah

3Department of Radiology, SUNWAY Medical Centre, 47500 Petaling Jaya, Selangor

a)Corresponding author: [email protected]
b)[email protected]
c) [email protected]

d) [email protected]

Abstract. Primary Open Angle Glaucoma (POAG) is a neurodegenerative disease of the eye that leads
to irreversible blindness. Whereas Alzheimer’s Disease (AD) is a common progressive neurologic
disorder that is characterized by initial memory impairment. Both POAG and AD are age-related
neurodegenerative diseases. As the progressive loss of neuron function on AD patients is becoming a
global health concern especially among the aging population, this study investigates the association
between POAG and AD based on the Medial Temporal Lobe Atrophy (MTA) and Posterior Atrophy
(PCA) scores in the brain. This semi-quantitative visual scoring is preferred since both the MTA and
PCA scores among early AD patients were found to increase before the atrophic changes become
generalized. This investigation is crucial since there has been limited studies on specific brain atrophy
locations particularly the temporal and parietal lobes for POAG cases. Using the T1-MPRAGE, the
MTA and PCA scores of patients who were initially diagnosed with POAG were obtained and
compared against the healthy control group. Subsequently, the Mann Whitney Wilcoxon Test analyses
were performed to determine the risk of developing AD. The findings showed that the PCA score
among POAG patients was found to be significantly different as compared to the control group (p-
value=0.026) with median score of 1±0.75, a score higher than the control group (0 ± 0.65). Based on
the results, POAG patients have relatively a higher chance of developing AD.

Keywords. Primary Open Angle Glaucoma, Alzheimer’s Disease, MTA & PCA Scoring, T1-
MPRAGE

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CMSC 05

HoH16StepsGL: A Clear-Cut Interactive Hypothesis
Testing Notes

Norah Tuah1, a), Roseline Michael1,b), Hazlenah Hanafiah 1,c)

1Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Sabah Branch,
Kota Kinabalu Campus, Locked Bag 71, 88997 Kota Kinabalu, Sabah

a)Corresponding author: [email protected]
b)[email protected]

c) [email protected]

Abstract. Univariate and Multivariate Hypothesis testing for sample mean and standard deviation as
well as testing for relationship among variables are commonly encountered in most statistical courses.
Prior case studies and observational analysis revealed that most of the students faced difficulty
understanding the concept of hypothesis testing. Hence, HoH16StepsGL is designed as an innovative
product to address this issue. The main objective of this product is to establish a straightforward
guideline of six steps hypothesis testing statistics. The novelty of HoH16StepsGL is to provide students
with an interactive and direct note equipped with comprehensive Standard Operating Procedure (SOP),
which is an auto pop-up on a single screen. Thus, the learning process will be more efficient and
effective by employing this faster and simpler working method. The significant criterion of this product
is its simplicity and ability to mediate 6 easy-to-understand steps of hypothesis testing, which cover test
statistics as decision rules (method 1) and p-value for the conclusion (method 2). The interactive and
clear-cut design of this product enables students to memorize the steps fast and effectively. There are
various advantages of this product, among which is that students can choose the correct statistical
methods and implement them easily using the Statistical Package for Social Science Software (SPSS).
Subsequently, students manage to explain the hypothesis statements correctly using the SOP before
making a decision. This impactful product is very beneficial to researchers and social science students
who are enrolled in statistical course.

Keywords. Hypotheses Testing, Standard Operating Procedure (SOP), Innovation, SPSS

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CMSC 06

Application of Fuzzy TOPSIS Method for Selecting Part-time
Lecturers: A Case Study of Faculty of Computer & Mathematical

Sciences UiTM Sabah Branch

Mazalan Sarahintu1, a), Munirah Rossdy1, b), Zamali Tarmudi2, c)

1Faculty of Computer & Mathematical Sciences, Universiti Technology MARA, Sabah Branch,
Kota Kinabalu Campus, 88997 Kota Kinabalu, Sabah, Malaysia

2Faculty of Computer & Mathematical Sciences, Universiti Technology MARA, Johor Branch,
Segamat Campus, 85000 Segamat, Johor, Malaysia

a)Corresponding author: [email protected]
b)[email protected]
c)[email protected]

Abstract. Universities need to hire lecturers who are knowledgeable and skillful to remain
competitive in the global arena. The proper and efficient selection of lecturers can ensure the
accomplishment of their established goals. This study aims to propose Fuzzy Technique for Order
Preference by Similarity to Ideal Solution (TOPSIS) method for hiring part-time lecturers in Faculty
of Computer & Mathematical Sciences, UiTM Sabah Branch. The alternatives and criteria weights
for selecting and ranking the lecturers are evaluated according to panels’ opinion and judgements.
Instead of using crisp values, triangular fuzzy numbers are employed to capture vagueness and
ambiguity in the panels’ judgements and preference. Results show that the Fuzzy TOPSIS method is
very useful due to its capability of dealing with vagueness, imprecision and uncertainty that occur in
the evaluation process. Thus, the proposed evaluation model can serve as an alternative tool for
selecting and ranking the potential candidates for lecturer jobs in university. Apart from that, the
model also provides a high flexibility where the procedures involved in the method can accommodate
further extension to make better choices in various situations of decision-making problems.

Keywords. Fuzzy TOPSIS, Fuzzy set theory, Triangular fuzzy number, multi-criteria decision
making, Lecturer selection.

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INSPIRATIONAL QUOTES

“IN THE LONG TERM, ARTIFICIAL
INTELLIGENCE AND AUTOMATION
ARE GOING TO BE TAKING OVER SO
MUCH OF WHAT GIVES HUMANS A

FEELING OF PURPOSE”
Matt Bellamy

“DATA IS THE NEW SCIENCE. BIG
DATA HOLDS THE ANSWERS”

Pat Gelsinger

“SHARING IS GOOD, AND WITH
DIGITAL TECHNOLOGY, SHARING IS

EASY”

Richard Stallman