bluuebunny/crossref_metadata_2025_split huggingface dataset:
Handling leukaemia imbalanced data using synthetic minority oversampling technique (SMOTE)
Authors: Chin F Y , Lim C A , Lem K H 
Published: August 2021

AbstractHigh dimensional data always lead to overfitting in the prediction model. There are many feature selection methods used to reduce dimensionality. However, previous studies in this area of research have reported that an imbalanced class raises another issue in the prediction model. The existence of the imbalanced class can lead to low accuracy in the minority class. Therefore, high dimensional data with imbalanced class not only increase the computational cost but also reduce the accuracy of the prediction model. Handling imbalanced class in high dimensional data is still not widely reported in the literature. The objective of the study is to increase the performance of the prediction model. We increased the sample size using the Synthetic Minority Oversampling Technique (SMOTE) and performing the dimension reduction using minimum redundancy and maximum relevance criteria. The support vector machine (SVM) classifier was used to build the prediction model. The leukaemia dataset was used in this study due to its high dimensionality and imbalanced class. Consistent with the literature, the result shows that the performance of the shortlisted features is better than those without undergoing the SMOTE. In conclusion, a better classification result can be achieved when high dimensional feature selection coupled with the oversampling method. However, there are certain drawbacks associated with the use of a constant amount of synthesis of SMOTE, further study on different amounts of synthesis might provide different performances.
Stock portfolio selection based on investors’ risk preference
Authors: Shahidin Ainon Mardhiyah , Othman Shahirulliza Shamsul Ambia , Razali Nur Syahirah Mohd 
Published: August 2021

Abstract
Stock portfolio investment gives investors the opportunity to engage in diversification among stocks which helps to achieve higher financial risk-adjusted return. A properly diversified stock portfolio should include stocks that have different economic variable such as interest rate, exchange rate and share price. It helps investors to achieve higher risk-adjusted return, nevertheless there are investors who love risk known as Risk Premium investors and Risk Averse investors who prefer lower risk. The risk value of stocks acts as an indicator in selecting stocks to be included in a portfolio. Risk value of stock portfolios is used in selecting stock portfolio that follows investors’ risk preference. This study forecast share price by using Geometric Brownian Motion and hence use the Variance Covariance to calculate Value at Risk of each stock and stock portfolio in future investment. The stock portfolios in this study are based on five sectors which are industrial-product, consumer, construction, technology, and trading and services. Thus, there are five stock portfolios that are produced for each type; Risk Averse and Risk Premium investors. Using the Value at risk of each stock portfolio, it is found that Stock portfolio from the Industrial Product Trading and Service sectors is the most suitable for Risk Averse and Risk Premium investors respectively. This study may serve as a guide for investors in creating and choosing stock portfolios for future investment based on their risk preference and also forecast its Value at Risk.
Identifying factors that affected student enrolment in Additional Mathematics for urban areas of Kuantan district
Authors: Chuan Z L , Liong C-.Y. , Yusoff W N S W , Aminuddin A S A , Tan E H 
Published: August 2021

Abstract
The skilful and qualified Science, Technology, Engineering and Mathematics (STEM) workforces are expected to be in high demand in the 21st digital economy. In Malaysia public education system, the principal key to STEM education is Additional Mathematics. However, the statistics depicted that the number of upper secondary students enrolled in Additional Mathematics have been severely delineated. Furthermore, the prerequisite to enrol in STEM and Technical and Vocational Education and Training (TVET) courses in tertiary education is achieving a minimum grade C for Additional Mathematics. Therefore, the principal objective of this article is to identify the significant factors that affected the upper secondary students enrolled in Additional Mathematics using Pearson’s chi-square test without Yates continuity correction and unadjusted odds ratio (OR). A validated questionnaire comprised nine potential factors that affected enrolment in additional mathematics was distributed to 389 Form Four students’ cohort 2020 from four selected urban government schools to pursue this objective. Based on the finding of this article, several initiatives might be taken by the policymakers, such as the teachers may enhancing and throughout the broad of STEM and TVET careers in the 21st digital economy era, while the students’ parents can participate in schools in building the communicating and coordinating mechanism. Consequently, the number of upper secondary enrolled in STEM education might be increased to pipeline the future STEM and TVET human capitals in sustaining and stabilising the national economy in the digital era.
Influence factors for proceeding with open and distance learning: UiTM Pahang sharing experience
Authors: Adnan Noor Izyan Mohamad , Ujang Suriyati , Syed W ahid Sharifah Norhuda , Azizah Y acob Nor , Zaini Azniza Ahmad , Adam Mohd Bakri 
Published: August 2021

Abstract
COVID-19 pandemic has affected almost all sectors in the world, including education. As an effort to break the chain of virus spreading, schools and higher institutions in most countries have stopped all physical classes for a while. Ministry of Education has directed a virtual learning to be conducted in schools and higher education during Movement Control Order was implemented in Malaysia to proceed the teaching and learning process. The virtual learning included online and offline learning which is called as open distance learning. Hence, the main objective of this study is to identify the factors that influence the Universiti Teknologi MARA Pahang Branch students to continue practicing the open and distance learning. A set of questionnaires was disseminated to all 7,363 students of Universiti Teknologi MARA Pahang, where a number of 1,181 responses had been received from the survey conducted with a responding rate of 16%. The demographic aspects of the students were represented by a descriptive statistic and the identification o f p o ssible f a ctors w a s u s ed t o b u ild a n e w analysis model using logistic regression analysis. According to the results obtained, there are six factors that influenced t he s tudents t o c ontinue p racticing O DL w hich a r e: 1 ) w orkstation, 2 ) internet access, 3) learning equipment 4) understanding learning video 5) frequentness of device usage and 6) exchange of final e x amination t o fi na l as se ssment. Ba se d on th e ov er all mo de l, 70.94% of the sample was correctly classified.
Primary school pupils’ images of mathematics
Authors: Ismail Nazihah , Abdullah Nur Hidayah Masni , Osman Roselah , Ramli Nazirah , Hilmi Zulkifli Ab Ghani 
Published: August 2021

Abstract
Images of mathematics are one of the critical elements of students’ knowledge in mathematics learning. The knowledge is formed through students’ various activities and experiences throughout their lives, including mathematics education events. This study examines the images of mathematics held by three primary school pupils of one small town located on the outskirt of Pahang. Data were collected through unstructured interview sessions and written question forms. One Year 4 male pupil, one Year 5 male pupil, and a Year 6 female pupil were selected using the convenience sampling method. Several matters related to the images of mathematics learning and metaphors related to mathematics are discussed in this paper.
A study of vehicle routing problem via trade-off ranking method
Authors: Jaini Nor Izzati , Aminuddin Adam Shariff Adli , Misni Farahanim , Zainuddin Zaitul Marlizawati 
Published: August 2021

Abstract
Vehicle routing defines selecting the minimum cost, distance, and/or time path from a depot to several alternatives for a goods or service to reach its destination. The objective of most routing problem is to minimize the total cost of providing the service. But other objectives also may come into play, particularly in the public sector. For emergency services, such as ambulance, police, and fire engine, minimizing the response time to an incident is of primary importance. A few routing algorithms do not use a deterministic algorithm to find the “best” route for a goods to get from its original source to its destination. Instead, to avoid congestion, a few algorithms use a randomized algorithm that routes a path to a randomly picked intermediate destination, and from there to its true destination. In this paper, the trade-off ranking method is used to solve for the vehicle routing treated as a conflicting multi-criteria problem. The integration of the trade-off ranking method into the vehicle routing problem gives another perspective on how to solve the problem, hence broadened the decision support system for the vehicle routing problem.
Multi-objective hybrid harmony search-simulated annealing for location-inventory-routing problem in supply chain network design of reverse logistics with CO2 emission
Authors: Misni F , Lee L S , Jaini N I 
Published: August 2021

Abstract
The advancement of supply chain network design in reverse logistics is gaining interest from the industries. In recent years, the multi-objective framework of the problem has been widely studied by researchers. This paper integrates three different levels of decision planning in supply chain network design: location-allocation problem for strategic planning, inventory planning management for tactical planning, and vehicle routing for operational planning. A location-inventory-routing problem based on the economic production quantity model with environmental concerns is considered. This study aims to minimise the total cost of operating facilities, inventory and distance travelled by the vehicles as the first objective while minimising the CO2 emission cost as the second objective. Due to the complexity of the problem, a non-dominated sorting and ranking procedure is applied into a Multi-Objective Hybrid Harmony Search-Simulated Annealing (MOHS-SA) algorithm to find the trade-off between these two objectives. Computational experiments on the benchmark instances indicate that the proposed MOHS-SA algorithm can produce well-distributed Pareto-optimal solutions for multi-objective problems.
A comprehensive review of hybrid game theory techniques and multi-criteria decision-making methods
Authors: Ibrahim Muhammad Akram Ramadhan , Jaini Nor Izzati , Khalif Ku Muhammad Naim Ku 
Published: August 2021

Abstract
More studies trend to hybrid the game theory technique with the multi-criteria decision-making (MCDM) method to aid real-life problems. This paper provides a comprehensive review of the hybrid game theory technique and MCDM method. The fundamentals of game theory concepts and models are explained to make game theory principles clear to the readers. Moreover, the definitions and models are elaborated and classified to the static game, dynamic game, cooperative game and evolutionary game. Therefore, the hybrid game theory technique and MCDM method are reviewed and numerous applications studied from the past works of literature are highlighted. The result of the previous studies shows that the fundamental elements for both frameworks were studied in various ways with most of the past studies tend to integrate the static game with AHP and TOPSIS methods. Also, the integration of game theory techniques and MCDM methods was studied in various applications such as politics, economy, supply chain, engineering, water management problem, allocation problem and telecommunication network selection. The main contribution of the recent studies of employment between game theory technique and MCDM method are analyzed and discussed in detail which includes static and dynamic games in the non-cooperative game, cooperative game, both non-cooperative and cooperative games and evolutionary game.
Solving incomplete fuzzy pairwise comparison matrix using fuzzy DEMATEL
Authors: Mohamad Daud , Zainuddin Nur Syafiqah 
Published: August 2021

Abstract
Analytic Hierarchy Process (AHP) is one of the multi-criteria decision-making methods that utilize pair-wise comparison in the evaluation process. The method is later extended to the fuzzy environment to cater and solve the problem of ambiguity and imprecise information known as fuzzy AHP. In the evaluation process, the issue of incomplete information has become a prevalent problem which may lead to invalid and biased results. The incomplete information occurs commonly due to inefficiency or negligence in handling the information and also the unavailability of the information for particular instances and situations. In this paper, a fuzzy DEMATEL based method of estimating incomplete values in fuzzy AHP is proposed. An imputation approach is used in the proposed method where the incomplete information is replaced with plausible and reasonable fuzzy values in the fuzzy AHP decision matrix. A step-by-step illustration of approximating the incomplete information will be given through a numerical example. It is found out that the estimation of the incomplete information in fuzzy AHP using fuzzy DEMATEL preserved the consistency of evaluation which is a vital validity instrument of evaluation for the fuzzy AHP.
Sharia-compliant stock preference using similarity-based Fuzzy Grey Relational Analysis
Authors: Shariff Jamilah Mohd , Mohamad Daud , Hasan Noorfahida 
Published: August 2021

Abstract
The introduction of Sharia-compliant stocks at Bursa Malaysia can be considered as a type of socially responsible investing mechanism, especially for Muslim investors. An increase in the public interest in stock investment has led to the introduction of methods of categorizing and selecting preferred stocks effectively. Fuzzy decision-making methods have also become an important approach due to the nature of ambiguous and imprecise available data in the decision-making process. Nevertheless, some simplifications are inevitable to reduce the complexity of the problem, and consequently, loss of vital information may occur. In this paper, a similarity-based fuzzy grey relational analysis (FGRA) is proposed to rank selected Sharia-compliant stocks. An element of similarity measure is introduced in the original FGRA to reduce the loss of information in the computation when the distance between fuzzy numbers is utilized. The similarity measure can capture more information compared to distance measure since, in the computation, additional geometrical features of fuzzy numbers will be incorporated. An improvised procedure of FGRA is offered and implemented to rank selected Sharia-compliant stocks based on some fundamental analysis criteria. A comparison is then made on the preference obtained by the proposed procedure with the original FGRA.
A view of MCDM application in education
Authors: Malik Durrani Aimi Abdul , Yusof Yuhani , Khalif Ku Muhammad Na’im Ku 
Published: August 2021

Abstract
The effectiveness of the teaching and learning process by educators plays a significant role for countries to prepare students’ potential in the forthcoming new industrial revolution (IR). However, the current COVID-19 pandemic and dynamic changes in the curriculum have created a significant shift of emphasis to educators. Hence, the teaching and learning process problems nowadays, including selecting appropriate effectiveness learning, have become a tough decision for educators. It can be solved using multi-criteria decision-making (MCDM) methods. The MCDM technique is widely applied and accepted in various fields but less in the teaching and learning context. This paper reviews and analyses the type of decision problems that were paid most attention to MCDM approaches, the adopted fuzzy set theory as well as inadequacies of those approaches. The purpose is to analyse and identify the literature review related to the applications of MCDM in education so new attributes and appropriate MCDM models for decision making can be suggested. The process involved comparing and analysing the MCDM application and fuzzy set theory in education by reviewing related articles in international scientific journals and well-known international conferences. Some improvements and more future works are recommended based on the inadequacies. The reviewed result may create an interest to the Ministry of Education (MoE) as it proposes teaching and learning process improvement, which will help to achieve greater satisfaction among educators and students.
Optimal Strategy Synthesis for Stochastic Boolean Games
Authors: Ghani Ahmad Termimi Ab , Higuchi Kojiro 
Published: August 2021

Abstract
In this study, we regard a classification of winning strategy and payoff function over infinite plays. The central goal is to examine the values of the game and then to determine the existence of optimal (∈-optimal) strategy. Furthermore, we are interested in the subject of what sort of optimal (∈-optimal) strategy exists. We first review on generalised reachability games and then we introduce a new game, called Boolean games and concentrate on games with a Boolean combination of the reachability games. The primary contribution is on the existence of ∈-optimal finite memory strategy of each player for any ∈ > 0. We also prove every player has no ∈-optimal memoryless strategy for some Boolean game.
Graph splicing rules with cycle graph and its complement on complete graphs
Authors: Abdul Razak M N S , Fong W H , Sarmin N H 
Published: August 2021

Abstract
Graph splicing system is a notion originally used to illustrate the one-dimensional string of DNA splicing in the form of a graph. A graph splicing system is associated with a graph splicing scheme where graph splicing rules are defined. A graph splicing rule restricts the possible cuts to occur on the edges of the initial graph(s) in a graph splicing system. The subgraphs of the initial graph are used in the splicing rules to determine the edges that will be cut from the initial graph. The concept of graph splicing system can be applied on various types of graph, hence generates components of spliced graphs depending on the types of the graph splicing rules used. There is a graph splicing rule called as a cutting rule which can be applied on both linear graphs and circular graphs where the graphs are transformed into Pseudo-Linear Form. However, this cutting rule has limited various possible cuts that can occur on the complete graph. Therefore, in this research, the original concept of graph splicing system is applied on complete graphs as the initial graphs. Also, graph splicing rules involving subgraphs of the initial graphs which are also complete graphs, are considered and applied in the graph splicing system. Furthermore, the generated spliced graphs are obtained through the graph splicing system.
Relative Commutativity Degree of Nonabelian Metabelian Groups of Order 32
Authors: Zakariah N A , Mohd Ali N M 
Published: August 2021

Abstract
A metabelian group is a group whose commutator subgroup is abelian. Similarly, a group G is metabelian if and only if there exists an abelian normal subgroup, A, such that the quotient group,
G
/
A
, is abelian. The scope of this research is only for nonabelian metabelian groups of order 32. The commutativity degree of a group G is the probability that two elements of the group G (chosen randomly with replacement) commute. This probability can be used to measure how close a group is to be abelian. This concept has been extended to the co-prime probability which is defined as the probability of a random pair of elements x and y in G for which the greatest common divisor for the order of x and order of y is equal to one. Furthermore, the study of relative commutativity degree of a subgroup H of a group G which is the probability of an element in H commutes with an element in G is included in this research. Previous researchers have determined the commutativity degree of nonabelian metabelian groups of order at most 32. Meanwhile, the co-prime probability and the relative commutativity degree of both cyclic and noncyclic subgroups H are obtained for nonabelian metabelian groups of order at most 30. Since there is no nonabelian group of order 31, thus in this research the co-prime probability and the relative commutativity degree of cyclic subgroups for nonabelian metabelian groups of order 32 are determined.
Consistency Relations of an Extension Polycyclic Free Abelian Lattice Group by Quaternion Point Group
Authors: Mohammad Siti Afiqah , Sarmin Nor Haniza , Hassim Hazzirah Izzati Mat 
Published: August 2021

Abstract
An extension of a free abelian lattice group by finite group is a torsion free crystallographic group. It expounds its symmetrical properties or known as homological invariants. One of the methods to compute its homological invariants is by determining the polycyclic presentation of the group. These polycyclic presentations are first shown to satisfy its consistency relations. Therefore, our focus is to show that this extension polycyclic free abelian lattice group by quaternion point group satisfy its consistency relations.
Elementary components of electroencephalography signals viewed as prime numbers
Authors: Fuad Amirul Aizad Ahmad , Ahmad Tahir , Nor Nur Aisyah Mohamad 
Published: August 2021

Abstract
The disabling aspect of epilepsy disease is that it seems to be erratic and random in nature. Electroencephalogram (EEG) serves as an essential non-invasive tool to diagnose and manage epilepsy, allowing the physiological manifestations of irregular cortical excitability to be demonstrated. Certain prior EEG features related to seizure onset may facilitate seizure pattern predictions through mathematical models. A better understanding of these patterns can positively improve epilepsy management and, in turn, improve the quality of life of epilepsy patients. Thus, the goal of the current paper is to show that elementary EEG signals during a seizure can be perceived as prime numbers. First, the recorded EEG signals are written as a product of their elementary components through the Krohn – Rhodes decomposition technique. Following this, every elementary component of EEG signal is expressed in terms of a summation of their simpler parts via the Jordan – Chevalley decomposition process. Conversely, some prime numbers are decomposed similar to Jordan – Chevalley decomposition of elementary EEG signals and presented as Pseudo – Goldbach Theorem. Finally, the results demonstrate substantial evidence that the EEG signals follow a pattern similar to that of the distribution of prime numbers among positive integers.
The non-zero divisor graph of ring of integers modulo six and the Hamiltonian quaternion over integers modulo two
Authors: Zai Nur Athirah Farhana Omar , Sarmin Nor Haniza , Khasraw Sanhan Muhammad Salih , Gambo Ibrahim , Zaid Nurhidayah 
Published: August 2021

Abstract
The study of graph theory was introduced and widely researched since many practical problems can be represented by graphs. A non-zero divisor graph is a graph in which its set of vertices is the non-zero elements of the ring and the vertices x and y are adjacent if and only if xy ≠ 0. In this study, we introduced the non-zero divisor graphs of some finite commutative rings in specific the ring of in tegers modulo 6, ℤ6 and ring of Hamiltonian quaternion, ℍ(ℤ2). First, the non-zero divisors of the commutative rings are found. Then, the non-zero divisor graphs are constructed. Finally, some properties of the graph, including the chromatic number, clique number, girth and the diameter are obtained.