Mathematical Sciences and Informatics Journal
MIJ is indexed in MyCite and DOAJ. The Mathematical Sciences and Informatics Journal (MIJ) (eISSN: 2735-0703) is a peer review , open-access international refereed journal. MIJ is published twice a year (May and November). MIJ accepts research papers in the field of Mathematics, Statistics, Actuary, Informatics and Computing. MIJ was initiated by researchers from the Faculty of Computer and Mathematical Sciences, UiTM Perak Branch, Tapah Campus in collaboration with other researchers from local and international universities. This journal is published by UiTM Press under the coordination of the Research Management Center (RMC), Universiti Teknologi MARA. MIJ is indexed in MyCite and DOAJ. MIJ is also available at Google Scholar. More about MIJ, feel free to visit our official website at https://mijuitm.com.my. CLICK HERE TO SUBMIT MANUSCRIPT
Enhancing MCDM with q-Rung Orthopair Fuzzy Dombi Generalized Heronian Mean
This paper presents a set of Dombi generalized Heronian mean operators for q-rung orthopair fuzzy numbers (qROFNs) and proposes a multi-criteria decision-making (MCDM) method based on these operators. The operational rules of qROFNs, grounded in the Dombi t-conorm and t-norm, are presented. A q-rung orthopair fuzzy Dombi generalized Heronian mean (qROFDGHM) operator is formulated based on these principles. A method for addressing MCDM problems utilizing qROFNs and the developed operators is proposed.
Copyright (c) 2025 ZAHARI MD RODZI https://creativecommons.org/licenses/by-nc-sa/4.0
Bipolar pythagorean neutrosophic hamacher heronian mean operators: a new framework in MCDM
This paper introduces the integration of Bipolar Pythagorean Neutrosophic Sets (BPNS) with advanced aggregation operators, namely the Hamacher and Heronian means. These integrations aim to improve the representation and synthesis of decision-making criteria. To this end, a novel framework called the Bipolar Pythagorean Neutrosophic Set-Generalized Hamacher Heronian Mean (BPNS-GHHM) is proposed. The proposed method is shown to satisfy all relevant properties
A Data-Driven SIR Model Analysis of COVID-19 Interventions in Malaysia
By the end of 2019, COVID-19 began spreading worldwide, posing a significant challenge to effective outbreak management. This study employs the Susceptible-Infected-Recovered (SIR) model to understand the transmission dynamics of COVID-19 in Malaysia, with a population of 34.3 million. Focusing on key phases implemented like the Movement Control Order (MCO) and Recovery Movement Control Order (RMCO), the research evaluates infection rates, recovery dynamics, and reproduction numbers using real-world data from the Johns Hopkins University COVID-19 Dashboard. During the MCO phase (18 March 2020 to 3 May 2020), the transmission rate was 0.0806, the recovery rate was 0.0309, and the basic reproduction number (R₀) was 2.607, with 90.52% of the population remaining susceptible post-phase. The RMCO phase (10 June 2020 to 31 March 2021) saw reduced transmission and recovery rates of 0.0880 and 0.0518, respectively, resulting in an R₀ of 1.698 and 68.97% of the population remaining susceptible. The peak infection rate during RMCO was significantly lower (1.698%), with the infection peak forecasted for 11 December 2020. These findings highlight the effectiveness of phased interventions in mitigating the epidemic's impact while emphasizing the SIR model's utility in providing timely insights during evolving public health crises
Copyright (c) 2025 Abdul Basit, JASNI MOHAMAD ZAIN, HAFIZA ZOYA MOJAHID, ABDUL KADIR JUMAAT, NUR'IZZATI HAMDAN https://creativecommons.org/licenses/by-nc-sa/4.0
Performance Analysis and Implementation of Hybrid Conjugate Gradient Method in Electromagnetic Tomography
Electromagnetic tomography (EMT) is a type of electrical tomography based on electromagnetic induction. Reconstructing images with EMT involves solving inverse problems, which are often poorly defined due to limited prior information about imaging features. Optimization methods such as conjugate gradient (CG), Quasi-Newton, and Steepest Descent can help minimize these problems. The conjugate gradient (CG) algorithm is an iterative method that efficiently handles equations with multiple inputs, saving time but requiring more memory. In this research, four hybrid CG methods which is MN-LAMR, MN-FR, MN-LS and MN-PRP are used to reduce the number of iterations (NOI) and CPU time, achieving excellent numerical performance. Based on numerical performances, MN-LAMR is the best method. Then, MN-LAMR is implemented into the EMT system to produce a new system called EMT-CG. The efficiency of the EMT and EMT-CG systems is evaluated based on error analysis using root mean square error (RMSE). The implementation of MN-LAMR into EMT improves its system efficiency according to the smaller number RMSE in comparison between EMT and EMT-CG. The findings highlight the hybrid CG method's capability within the EMT system which will be useful in enhancing the medical field technology.
Copyright (c) 2025 Michelle Ubong Sari, Dzaihan Dzul, Nurfatihah Anizan, Nur Syarafina Mohamed, Norhaslinda Zull Pakkal https://creativecommons.org/licenses/by-nc-sa/4.0
Online Social Sentiment Analysis: Discerning Customer Satisfaction via Twitter Reviews on Malaysia’s Courier Service
As e-commerce continues to grow, customers frequently encounter issues with courier services such as late deliveries, tracking problems, and unsatisfactory customer support. Although courier services are widely used, there is no dedicated platform that helps users choose the best provider based on social media sentiment. This study investigates customer satisfaction with courier services in Malaysia using Twitter reviews, focusing on three prominent providers: PosLaju, GDex, and DHL. A web-based application was developed using the Flask framework in Python and deployed on the Heroku platform. Sentiment analysis was performed using the TextBlob library, which classifies tweets into positive, negative, or neutral categories. TextBlob was selected for its ease of use and effectiveness in handling basic natural language processing tasks such as polarity detection and phrase extraction. The sentiment results were visualized to reveal trends in user feedback. The analysis showed that PosLaju had the lowest positive sentiment, with only 4.1 percent, and a relatively high negative sentiment of 14.9 percent. DHL received the highest positive sentiment at 39.6 percent and 20.8 percent negative, indicating a stronger approval among users. GDex showed moderate levels of both positive and negative feedback. This study provides valuable insight into customer perceptions of major courier services in Malaysia. By highlighting sentiment trends based on real user experiences from Twitter, the platform can assist future customers in selecting the courier service that best matches their needs.
Copyright (c) 2025 Nur Azmina Mohamad Zamani, Ahmad Muhyiddin Yusof, Nurul Zawani Muhamad Shukri https://creativecommons.org/licenses/by-nc-sa/4.0
Comparing Stochastic Models for Forecasting Mortality in Malaysia: Lee-Carter, Booth-Maindonald-Smith, and Age-Period-Cohort
Problem: The Human Life Table Database (HLD) provided the death rate data utilised in this study. With an emphasis on gender disparities and applying data from 2001 to 2020, this study analyses the problem of selecting the most accurate stochastic model for forecasting mortality rates in Malaysia. Aims/Objectives: This study compares the Lee-Carter, Booth-Maindonald-Smith, and Age-Period-Cohort models to determine which stochastic model is more effective in predicting gender-specific death rates in Malaysia between 2021 and 2026. Methodology/approach: The Human Life Table Database (HLD) included mortality rates for male and female participants aged 0 to 80. The data were divided into 5-year age intervals from 2001 to 2020. The Lee-Carter model, the Booth-Maindonald-Smith model, and the Age-Period-Cohort variant of the Lee-Carter model are the three stochastic models that the study applies to this dataset. The residuals and error data were analysed to determine how well each model predicted mortality rates. The model producing the lowest error values was determined to be the most suited model for forecasting mortality trends. Comparisons were conducted across the models to assess the accuracy and robustness of the models in representing the mortality dynamics for both genders in Malaysia. Results/finding: The Lee-Carter model was identified as the most accurate stochastic model for forecasting mortality rates in Malaysia from 2001 to 2020, as it produced the lowest error values compared to the other models.
Nurul Akmar Binti Mohamad Fadzill Mohamad Fadzill
Copyright (c) 2025 SHAMSHIMAH SAMSUDDIN, Natasya Mazlan, Nur Aqilah Nadiera Nazhar, Nurul Akmar Mohamad Fadzill , Nurul Izzah Mohamad Naser https://creativecommons.org/licenses/by-nc-sa/4.0
Assessing Flood Risk through Frequency Analysis at Sayong River Station
This research investigates extreme flood events at Sayong River Station using two statistical distributions: the Generalized Logistic (GLO) and Generalized Extreme Value (GEV) distributions. The study employs the L-moment method for parameter estimation and evaluates quantile estimates for return periods of 10, 50, and 100 years. The primary objective is to determine which distribution provides a more accurate representation of extreme flood behavior. Quantile estimates derived from the GLO distribution are 197.3153 m³/s for the 10-year return period, 363.8308 m³/s for the 50-year return period, and 469.9711 m³/s for the 100-year return period show better alignment with observed data compared to the GEV distribution. The GLO distribution's superior performance indicates its enhanced ability to capture the tail behavior of extreme floods, providing more reliable estimates for flood risk management. The findings emphasize the importance of selecting an appropriate distribution model for accurate flood risk assessment. The efficacy of the GLO distribution in representing extreme values underscores its appropriateness for forecasting extreme flood magnitudes and providing guidance for infrastructure design and flood mitigation measures.
Copyright (c) 2024 Nur Diana Zamani, BASRI BADYALINA, Muhammad Zulqarnain Hakim Bin Abd Jalal, Rusnani Mohamad Khalid, Fatin Farazh Ya’acob, Kerk Lee Chang https://creativecommons.org/licenses/by-nc-sa/4.0
E-Learning Application based on Gagne’s Instructional Design Model (E-DBLEARN)
Learners often struggle with the complex and interconnected terminology in database environments and data modeling, leading to difficulties in understanding and applying key concepts effectively. In addition, a preliminary study has revealed that inadequate classroom facilities, varying learning styles, and the use of external resources that are not tailored to the syllabus have negatively impacted the understanding of theory-based topics. This study aims to achieve several objectives: identifying requirements of an e-learning application for Introduction to Database, design and develop the e-learning application and evaluating the e-learning application’s functionality and usability. This research has been initiated by preliminary analysis on the application requirements based on literature review and surveys. The design phase followed, producing essential diagrams which are navigation map and storyboards. The development was done utilizing Adobe Animate, Adobe Premiere Pro, Adobe Audition and Adobe Photoshop for producing the application for learning database. Lastly, the functionality and usability of the application was verified through testing. Usability testing involved expert evaluation with input from three experts. The results acquired give a positive indicator for further implementation. Further evaluation with 30 respondents from the target users has produced results indicated high satisfaction with the application’s overall usability, particularly in visual design and self-assessment and learnability constructs, which achieved the highest mean scores of 4.80 with standard deviations of 0.41 and 0.48, respectively. In conclusion, E-DBLEARN offers university students studying database courses an interactive, multimedia-rich platform expected to boost engagement, understanding, and self-directed learning, while equipping lecturers with an effective tool to teach theoretical concepts in the database courses. Gagne’s Instructional Design Model was incorporated to ensure that learning is effective, efficient, and structured by guiding the instructional process through a systematic approach.
Copyright (c) 2024 Nor Azila Awang Abu Bakar, Fatin Najwa Kamal, Siti Nurul Hayatie Ishak, Norlina Mohd Sabri https://creativecommons.org/licenses/by-nc-sa/4.0
Application Of Cubic Trigonometric Hermite Interpolation curve With Shape Parameters In 2 Dimensional Objects
Problem: Achieving accurate mathematical representations of an object's geometry for computer-aided design and manufacturing is complex. Designing both objects demands a method that provides the necessary flexibility and smoothness in curves, which traditional methods lack of flexibility and smoothness in curves needed for precise and efficient design. Aims/Objectives: The main objective is to explore and implement cubic trigonometric Hermite interpolation as a method for constructing two-dimensional objects. Next, to discussed the properties of this interpolation method and to determine the best value of the shape parameter that produces smooth curves Methodology/approach: Cubic trigonometric Hermite interpolation is used for constructing two-dimensional objects. This process is conducted using Mathematica. The different values of the shape parameter are used to achieve the desired curve characteristics in the geometric models. Results/finding: The correct images of the two dimensional objects are also located and the suitable shape parameters can be obtained after studying the behavior of the curve using free parameters. Two dimensional object can be formed using cubic trigonometric Hermite interpolation without making any easy blunders or errors. Implication/impact: The impact of this project lies in its potential to improve geometric modelling by providing the best value of shape parameter that enhances the precision and efficiency of creating two-dimensional geometric models. This can significantly benefit technical drawing, computer-aided design, and manufacturing by offering a more flexible and accurate way to represent objects' geometry.
Copyright (c) 2024 NURSYAZNI MOHAMAD SUKRI, FARAH NABILAH AZMI, NOOR KHAIRIAH RAZALI , SITI MUSLIHA NOR-AL-DIN https://creativecommons.org/licenses/by-nc-sa/4.0
COMPARATIVE ANALYSIS OF EULER AND RUNGE-KUTTA FEHLBERG METHODS IN SOLVING THE LOTKA-VOLTERRA COMPETITIVE MODEL
Problem: Based on articles written by Razali and Abdullah (2013), exclusion often occurs at a slow rate. Therefore, it was difficult to determine if equilibrium and stability exist. Equilibrium is the state of an ecosystem in which all components are in balance with one another. In addition, equilibrium species supposedly survive through a competitive survival strategy rather than through reproduction or dispersal to survive in harsh conditions where food resources are scarce. Unfortunately, based on the principle of competitive exclusion proposed by Gause (1934) which states that two species competing for the same resources cannot coexist, one will drive out. Aims/Objectives: 1) To analyse the competitive interactions between lions (Panthera leo) and leopards (Panthera pardus) in the Sabi Sand Game Reserve, South Africa by comparing among exact solutions using Euler and RKF methods on the Lotka–Volterra Competitive model. 2) To discuss the impact of carrying capacity (capability survival) of dynamic behaviors in competition between two different species. 3) To analyze equilibrium and stability of the competition between two species depending on the initial conditions. Methodology/approach: This study used data from Balme et al. (2017) to examine competitive interactions between two top predators, lions (Panthera leo) and leopards (Panthera pardus) from 2010 to 2015 in the Sabi Sand Game Reserve, South Africa. This study will test whether lions, as the dominant competitor, will limit the distribution and abundance of leopards by using dietary data collected concurrently on the 2 species. Dietary overlap between lions and leopards was initially limited, with lions targeting large- to very large-sized prey and leopards small- to medium-sized prey. The Euler and Runge-Kutta Fehlberg (RKF) methods will be applied for solving this model and subsequently compare the simulation results with their exact solutions. It is anticipated that these numerical approximations will undertake to find out approximate solutions to nonlinear problems. Numerical approximation tests the reliability and precision of both methods applied to the logistic equation. This result is supported by computations carried out using the Mathematica 13.2 software. Results/finding: The findings indicate that the RKF method provides an accurate approximation, outperforming the Euler method. The results demonstrate that a larger carrying capacity is associated with a greater ability for a species to thrive and survive in competitive environments. Carrying capacity refers to the maximum population size a species can sustain indefinitely, considering factors like food, habitat, water, and others. During the curve-fitting procedure, it was observed that leopards have a higher carrying capacity compared to lions. Therefore, it can be inferred that the population of leopards is not significantly affected by the presence of lions. Implication/impact: The study will be beneficial to future researchers who engage with nonlinear differential equations, mathematical biology, and numerical techniques. By utilizing data stimulation to mimic real-world problems. As suggestion, this study can provide insights and solutions for related issues faced by the Department of Wildlife and National Malaysia. For example, it can aid in the restoration of large carnivores to support struggling ecosystems in Malaysia (Ripple, 2014). Furthermore, this study will contribute to the verification of the theory of exclusion and its applicability in various competitive scenarios. It will help determine whether both predator species, lions, and leopards, can coexist while undergoing competition. Additionally, the study will demonstrate the practical application of numerical approximation as a predictive tool, enabling researchers to determine the outcome of interspecific competition without the need for extended experimental periods. Moreover, these findings will enhance our understanding and provide illustrations of how numerical approximation can be utilized to predict competition outcomes, aiding researchers in determining which species may prevail in different interspecific competition scenarios.
Copyright (c) 2024 NURIZATUL SYARFINAS AHMAD BAKHTIAR, Nur Hidayah Abd Rahaman, Hafizah Hajimia, Nur Fatihah Fauzi, Nur Izzati Khairudin https://creativecommons.org/licenses/by-nc-sa/4.0
Reliability and Construct Validity Assessment of the Student Competency Questionnaire among Final Year Diploma Students: A Statistical Analysis Approach
The university strives to provide students a curriculum that is pertinent and taught by educators with exceptional delivery methods, in a stimulating and dynamic learning setting. The objective is for students to graduate from the institution as individuals who can positively impact society, establish businesses, and assume leadership roles in the professional realm. The objectives of this research are to develop the Student Competency Questionnaire (SCQ) and evaluate its reliability and validity. The evaluation followed classical test theory, focusing on reliability, construct validity, and content validity. A postal questionnaire containing 49 items was sent in October 2022 to a sample of 59 final-year diploma students from various programs. Three experts in education, statistical modeling, and decision-making evaluated the content validity of the scale. The Content Validity Index (CVI) for all constructs ranged from 0.96 to 1, exceeding the threshold of 0.70, indicating that the items are 'content valid.' Cronbach's alpha values showed a high level of internal consistency, all exceeding 0.90. Additionally, all items within each construct were highly related to one another, with correlations exceeding 0.30. This research demonstrates that the Pillar 1 education 5.0 @ UiTM frameworks effectively capture essential skills for students' academic and professional development, enhancing their employability. The focus on Personal, Adaptive, Digital, 21st Century, and Social competencies, along with student satisfaction, ensures students are equipped with diverse skills needed to thrive in dynamic environments. Overall, UiTM's approach prepares students for success in their future careers and personal lives.
Students Competencies Reliability Validity Questionnaire Evaluation Cronbach’s Alpha
Copyright (c) 2024 Nor Faezah Mohamad Razi, Dr.Norhayati https://creativecommons.org/licenses/by-nc-sa/4.0
An Evaluation of Online Food Delivery Application: Fuzzy Analytical Hierarchy Process
Food delivery is one of the businesses reporting growth rates after the COVID-19 pandemic. Due to social isolation and extensive lockdowns worldwide, individuals who once dined out now choose online food delivery. To keep up with the ever-changing market dynamics, the service provider must be aware of various measurements and aspects related to sustainable growth. Therefore, this study aims to determine the criteria for evaluating online food delivery applications, calculate the weight for criteria, and rank the online food delivery applications according to the most preferred by the customers. This study uses a multi-criteria decision-making (MCDM)-based framework which is the Fuzzy Analytic Hierarchy Process (FAHP). The FAHP is used to produce weights for criteria by applying fuzzy set theory to the linguistic evaluation statements of experts and ranking the online food delivery applications according to the customer's preference. The findings indicate that Foodpanda is the most preferred food delivery application, followed by GrabFood and McDelivery. The most crucial main criterion is economics, with delivery cost as the priority sub-criteria. The second most important criterion is technology, the third is service quality, and the last is social and environmental. This study is useful for the service provider in improving the criteria that will most affect the customer, as well as for the customer to wisely choose the e-service application that meets their demand.
Copyright (c) 2024 Nur Solihah Khadhiah Abdullah https://creativecommons.org/licenses/by-nc-sa/4.0
Complex Network Analysis on NASDAQ Stock Market around COVID-19
Problem: The United States plays an important role in the global economy, and the COVID-19 pandemic significantly affected the U.S. stock market. Over the two decades, numerous studies have incorporated complex network analysis to analyze the stock market, but there is a lack of study in identifying anomalies in network structures during financial crises. Aims/Objectives: The main objective of this research is to implement complex network analysis in examining the changes in the network structures and centralities of the NASDAQ stock networks at periods around the COVID-19 pandemic. Methodology/approach: The opening prices of the stocks under NASDAQ index in the last two quartile of 2019 and the first quartile of 2020 were collected from Yahoo Finance. The collected data was parsed into edges lists which was then used to construct multiple stock networks. The structures of the stock networks were analyzed using topological metrics such as network density, average clustering coefficient, average path length, network centralizations, and modularity of community structure. The centrality scores of the stocks in the networks were calculated and they were ranked according to the scores. Results/finding: The results show abnormal values in the number of edges, network density, betweenness centralization, and modularity of the community structure in the initial stages of the COVID-19 pandemic. However, no significant anomalies are observed in the average clustering coefficient, average path length, degree centralization, and closeness centralization. Meanwhile, degree centrality proves effective in identifying influential stocks, while closeness and betweenness centralities are found to be less suitable for this particular purpose in the networks used in this study. Implication/impact: This paper provides insights on the changes within the stock market at both micro and macro levels around financial crisis, where the anomalies serve as indicators of an impending financial crisis.
Copyright (c) 2024 Jia Hou Chin, Nor Aziyatul Izni https://creativecommons.org/licenses/by-nc-sa/4.0
Predicting Default and Non-Default Firms using Discriminant Analysis: Adaptation of KMV-Merton's Default Probabilities and Financial Ratios
The KMV-Merton model provides conceptual determinants for predicting firms' default risk, but its accuracy was tested long ago, and it contains insufficient statistics for default prediction. Therefore, previous literature adapted the KMV-Merton model into a statistical model involving financial ratios to improve its predictive capabilities. Discriminant Analysis (DA) is a widely used statistical model for predicting financial distress. The objectives of this study are to identify financial ratios significant to KMV-Merton's default probabilities using DA, to predict default and non-default firms using the DA model obtained, and to compare the performance of the KMV-Merton and DA models in predicting default risk. The study uses 11 years of data from Malaysian publicly listed firms, applying the KMV-Merton model and stepwise DA in SPSS. DA identifies the significance of selected financial ratios to firm default, with KMV-Merton's default probabilities as the dependent variable, forming a discrimination function to predict default and non-default firms. Credit ratings and Type 1 and Type II errors are used to compare model performance. The DA using SPSS reveals a discriminant function with net profit margin and return on assets significantly related to KMV-Merton's default probabilities. The DA model is more biased in predicting non-default firms due to the need for more information on default firms, yet it slightly outperforms the KMV-Merton model. This study offers guidance on adapting KMV-Merton's default probability estimates with financial ratios in the DA model and highlights the significant financial ratios related to KMV-Merton's default probabilities.
Copyright (c) 2024 Norliza Muhamad Yusof, Nur Ain Al-Hameefatul Jamaliyatul, Nurul Afiqah Zainuddin, Izza Suraya Zulhazmi, Muhamad Luqman Sapini https://creativecommons.org/licenses/by-nc-sa/4.0
Determinants of Smartphone Prices using Backward Elimination Technique in Multiple Linear Regression
Problem: The rapidly evolving market for smart gadgets causes smartphone prices to vary widely, frequently posing challenges to what consumers expect and can afford. Therefore, understanding the complex interrelationship of factors that determine smartphone prices has emerged as an important subject for study in an era defined by technological developments. Aims/Objectives: This study seeks to identify the factors that influence the pricing of smartphones. Methodology/approach: The study focused on various factors, including the battery capacity, camera quality, screen size, charging speed, device weight, and age in months. The primary data for the research came from the Global System for Mobile Communication (GSM) online marketplace, comprising sixty smartphones selected through a simple random sampling technique. We initially developed a multiple linear regression model with SPSS and then refined it using backward elimination. Results/finding: The results highlight the strong influence of several characteristics on smartphone pricing, namely battery capacity, charging speed, weight, and model age. Interestingly, the examination of six variables revealed that camera and screen size had no effect on price. Implication/impact: The knowledge acquired from this quantitative analysis not only advances our comprehension of the interplay between technology and consumer demand but also has implications for manufacturers, policymakers, and consumers who desire to navigate the ever-changing sphere of smartphone pricing.
Copyright (c) 2024 Sarah Yusoff, Muhammad Hazwan Mohd Hazhar, Dzul Dzaihan Dzul Dzailani, Nuralya Sofea Hairulanuar, Nurfatihah Anizan https://creativecommons.org/licenses/by-nc-sa/4.0
Efficiency Of Malaysian Life Insurance Company Using Two-Stage DEA Method
The insurance industry provides unique financial services for the growth and development of every country. The efficiency measurement in the insurance companies may increase the quality of their operations and assist in identifying the inefficacy stages for future improvements. This research intends to evaluate the efficiency of 12 life insurance companies in Malaysia by applying the Traditional DEA method as well as the Two-Stage DEA method in the year 2021. Traditional DEA views the actions of decision-makers as a black box, overlooking the intermediate process which is unsuitable for network systems in the insurance industry. The production process of a life insurance company is divided into two sub-processes, which are operational and profitability stages, suitable to be evaluated by the Two-Stage DEA method. This method calculates the efficiency score of the DMUs by equally considering the intermediate phases. The model was executed using Lingo 20.0 software yielding efficiency scores ranging from 0 to 1. The findings revealed that five companies performed efficiently throughout the whole production process under Traditional DEA. However, none of these five companies has an overall efficiency score of 1 under the Two-Stage DEA. This is because none of those companies are efficient in both sub-processes. This reveals the limitations of Traditional DEA thus offers valuable insights to Malaysian life insurance companies on the effectiveness of Two-Stage DEA in assessing operational and profitability efficiencies. This study aids companies identify areas for improvement and encourage benchmarking against efficient competitors.
Copyright (c) 2024 Nur Rasyida Mohd Rashid, Nur Diyana Awanis Razaly, Nurul Nadia Saharuddin, Muhamad Faris Iskandar Mohamad Fauzi https://creativecommons.org/licenses/by-nc-sa/4.0
Total Variation-based Active Contour Model for Medical Images
The Active Contour Model (ACM) is a mathematical model in image processing that is commonly utilized to partition or segment an image into specific objects. The segmentation method in region-based ACM can be categorized into two classes: global ACM and selective ACM Selective ACM isolates a specific target item from an input image, which is more advantageous than the global ACM due to its proven use, particularly in medical image analysis. However, the selective ACM appears to produce poor outcomes when segmenting an image with uneven (inhomogeneous) intensity. Additionally, the current selective ACM that uses the Gaussian function as a regularizer generates a non-smooth segmentation curve, especially for images containing noise. This study introduces a new selective ACM that is designed to segment medical images with inhomogeneous intensity levels. The model incorporates a Total Variation term as a regularizer, distance function, and local image fitting concepts. The Euler-Lagrange (EL) equation was given to solve the suggested model, which is approximately 5% more accurate with a processing time that is around three times faster than the existing model, as shown by numerical testing. The suggested mathematical model can be advantageous for the image analysis community, particularly in the medical industry, to automatically segment a specific object in a medical image.
Copyright (c) 2024 ABDUL KADIR JUMAAT https://creativecommons.org/licenses/by-nc-sa/4.0
Optimizing Procurement System Using Nielsen’s Heuristics
A fitness center grapples with significant challenges related to administrative errors, prolonged purchase cycles, and supplier management issues, resulting in escalated costs and operational inefficiencies. To address these hurdles, this project aims to develop a procurement system for this fitness center, targeting the optimization of procurement activities, improvement of inventory management, and facilitation of smoother interactions with suppliers for managers, staff, and suppliers alike. The objective of this study was to identify the requirements for the procurement system, design and develop the system with integrating Nielsen's heuristics. Furthermore, system evaluation has been conducted to test its functionality and usability to the target users. Utilizing an adapted waterfall model as the framework, the system's scope encompasses user registration, login procedures, purchase order submission, invoice generation, and equipment maintenance and management. The evaluation results demonstrated that the system meets all requirements outlined in the test plan. Additionally, feedbacks from both users and experts have been integrated to further refine the system. Implementation of this system will make the procurement process smoother and more organized. By prioritizing usability, efficiency, and user satisfaction, the system has the potential to optimize procurement activities, reduce errors, and ultimately improve the overall functioning of the fitness center.
Copyright (c) 2024 SITI NURUL HAYATIE ISHAK https://creativecommons.org/licenses/by-nc-sa/4.0
Forecasting the Air Pollution Index: A Case Study in Shah Alam, Selangor
Abstract can't be placed here as the system will loading and produced error.
Copyright (c) 2024 Isnewati Ab Malek https://creativecommons.org/licenses/by-nc-sa/4.0
The Impact of Predator Attack Behaviour on Interactions in Two Prey an One-Predator Systems
This research explores a three-species model of prey and predator interactions, which includes primary and secondary prey and a predator. The main concern is the potential disturbance caused by uncontrolled predator attacks, which can harm the coexistence of species and disrupt the entire food chain system. Thus, this research aims to analyze the impact of predator attacks on primary and secondary prey, focusing on coexistence dynamics or potential extinction within the system. The approach involves formulating a simplified ordinary differential equation for a two-prey and one-predator system, calculating equilibrium points, and performing theoretical stability analysis. Numerical simulations are executed using Maple and MATLAB software to validate the theoretical findings, providing a strong foundation for the research outcomes. The main findings indicate that high-intensity predator attacks can result in the extinction of prey populations, while moderate-intensity attacks facilitate the coexistence of all species. This research holds significant implications for ecological conservation, offering insights that can guide strategies for managing predator populations and influencing ecosystem stability. This study provides a basis for well-informed ecosystem management and conservation initiatives by clarifying the conditions under which coexistence or extinction occurs.
Copyright (c) 2024 Zati Iwani Abdul Manaf, Suziana Aida Othman, Wan Nurul Husna Wan Nordin https://creativecommons.org/licenses/by-nc-sa/4.0
Comparative Study of the Selection of the Best Contractor Using Fuzzy Weak Autocatalytic Set and Analytic Hierarchy Process
The prevalence of pairwise comparison in decision-making processes, particularly in Multiple Criteria Decision Making (MCDM) contexts, and the need for effective techniques to address MCDM challenges in the context of contractor selection. The objectives of this research are; 1) To explore and apply the Fuzzy Weak Autocatalytic Set (FWACS) technique in the problem of contractor selection. 2) To compare the outcomes of FWACS with those obtained using the Analytic Hierarchy Process (AHP). This research has been initiated by a preliminary analysis of the characteristics of the theorem based on a literature review. The methodology will start with the utilization of the FWACS technique, followed by the conception of a fuzzy graph through a comparative assessment of a set of alternatives. Next is a comprehensive comparison of outcomes between FWACS and the Analytic Hierarchy Process (AHP), and lastly, a sensitivity analysis to substantiate the stability and consistency of decisions derived from FWACS. The decisions derived from FWACS exhibit stability and consistency. In comparison with AHP, it's confirmed that FWACS not only matches established methods but also excels in handling uncertainties typical of real-world situations. FWACS, especially within the fuzzy framework, stands out for effectively managing uncertainty. This advantage makes it particularly useful for complex decision problems involving imprecise or ambiguous information. The practical application of FWACS in addressing contractor selection problems. The substantiated stability and consistency of decisions derived from FWACS make them comparable to those derived from AHP.
Copyright (c) 2024 Siti Salwana Mamat, Zarith Sofiah Othman, Noraini Ahmad https://creativecommons.org/licenses/by-nc-sa/4.0
Eccentric Connectivity Index of the Non-Commuting Graph Associated to the Dihedral Groups of Order at Most 12
A topological index is a numerical value or invariant in mathematics that characterizes specific topological aspects of a space, manifold, or mathematical object. Topological indices are used to differentiate between topological spaces or to capture specific characteristics of their structure. Meanwhile, a non-commuting graph is a graph in which two unique vertices are adjacent if and only if they do not commute, that is , and it consists of the non-central elements set in a group as a vertex. In this paper, Maple software constructed the non-commuting graph of the dihedral groups of order at most 12. Then, the degree and distance of the non-commuting graph for dihedral groups are found. The eccentric connectivity index of the non-commuting graph of dihedral groups of order at most 12 is computed using its definition. As a result, the eccentric connectivity index of non-commuting graphs for dihedral groups increases as the order of the groups increases. In real life, one of the eccentric connectivity index's effects is that it can be utilized as a chemical descriptor in drug discovery to predict biological activities such as binding affinities to target proteins or enzymes.
Copyright (c) 2024 Zulfazleen Natasha binti Zulkiflee, Nur Idayu Alimon https://creativecommons.org/licenses/by-nc-sa/4.0
Operational Cost Optimization on Solid Waste Collection Using Goal Programming
Waste collection is the Waste management, comprising storage, collection, transportation, and disposal, is the most expensive aspect of waste management, involving resources in strategy, execution, and oversight. Even in Perlis, the smallest state in Malaysia, waste management has become a concern due to population growth and increased industrial activities. This study aims to identify the most cost-effective approach for a private company's monthly waste collection in Perlis, utilizing goal programming to determine the optimal cost. Data from E-Idaman Kangar Sdn. Bhd, a private company managing solid waste in Perlis, was utilized. The goal is to achieve optimization by formulating an objective function and utilizing Lingo software version 18.0. The study targets five goals: minimizing labor, collection, vehicle, and consumable costs, as well as minimizing the financial statement of operation for each route. The research results indicate that E-Idaman Kangar's collection expenses are already at an optimal state. The analysis reveals that the cost of each vehicle involved in the collection is optimized. The objective value indicates that the total expenditure can still be reduced by RM3, representing a 0.01% decrease. In conclusion, the organization demonstrates efficient waste collection practices.
Copyright (c) 2024 Diana Sirmayunie Mohd Nasir, Suzanawati Abu Hasan https://creativecommons.org/licenses/by-nc-sa/4.0
An An Illustration of Bilah Keris Luk 7 with Bezier Cubic Curve and Cubic Polynomial Curve
The Bezier cubic curve and cubic polynomial curve are used to illustrate the bilah keris, commonly known as a 'blade dagger'. Keris is a popular weapon in Malaysia, originally designed for battle. Currently, it has evolved into a conventional craft with aesthetic characteristics. Keris has wavy edges known as luk, which typically come in odd numbers like three, five, seven, eleven, and thirteen. A luk is a curve on a keris defined by various equations. Traditionally, each luk represents a distinct meaning and symbolism. The keris luk 7 represents authority and charisma in government. However, mathematically, this study examined the various curves on the luk of the bilah keris. Two distinct equations are applied to create the graphic image for the blade of the keris with 7 luk. The equations of curves representing different shapes were defined using MAPLE software, and the coordinates were obtained from the GetData Graph Digitizer. The distinctive curve on the bilah keris model is determined using mathematical equations, which represent two distinct visualisations of the keris. As a result, these eight specific curves demonstrate the flexibility of the curves with the coordinate points acting as the control points on the image.
Copyright (c) 2024 MASNIRA RAMLI, Suziana Aida Othman, Ahmad Nizam Abd Khairudin, Nor Mahfuzah Mazlan, Azma Shahaiman Azimin https://creativecommons.org/licenses/by-nc-sa/4.0
An Integer Linear Programming Approach to the Travelling Salesman Problem for Optimizing Self-Drive Tourist Routes in Kuala Lumpur
Problem: Self-drive tourism offers tourists the flexibility to explore destinations at their own pace, utilizing private transport. However, it is essential to underscore the significance of thorough planning for a successful and enjoyable experience. Aims/Objectives: The objective of this research is to explore the concept of travelling salesman problem and its application in optimizing travel routes for self-drive tourists visiting Kuala Lumpur. Methodology/approach: The study employed an integer linear programming (ILP) model to propose efficient routes that connect all seven notable points of interest in Kuala Lumpur, including the Petronas Twin Towers, Batu Caves, Central Market, Merdeka Square, Bukit Bintang, KL Tower, and Titiwangsa Lake Garden. Results/finding: Implementation of ILP for suggested routes results in reduction of approximately 36.86% in transportation distance, ultimately leading to a decrease in transportation costs. This demonstrates the effectiveness and efficiency of the proposed approach, enabling tourists to maximize their experience while minimizing time and energy spent navigating congested or inefficient roads. Implication/impact: This research emphasizes the importance of self-drive tourism and the application of an ILP model in optimizing travel routes for tourists in Kuala Lumpur. By following the suggested routes, visitors can efficiently navigate the city's diverse neighborhoods and transportation options, while enjoying its notable attractions. The significant reduction in transportation distance achieved through this approach highlights its effectiveness in enhancing the travel experience in Kuala Lumpur.
Copyright (c) 2024 Nur Azirah Suliman , Noorezatty Mohd Yusop, Nurfaqihah Athirah Mat Janggi , Nur Shamira Shamimi Kamaruddin , Nora Mohd Basir https://creativecommons.org/licenses/by-nc-sa/4.0
Forecasting the CO2 Emissions at Malaysia using Group Method of Data Handling
This study utilizes the Group Method of Data Handling (GMDH) model to anticipate CO2 emissions, providing a comprehensive analysis of various input variables, training methods, and forecasting stages. The research uncovers distinct patterns in the behavior of input variables X1, X2, and X3 during both training and forecasting. Notably, X2 consistently exhibits strong performance, whereas X1 and X3 face difficulties, particularly in the forecasting phase. The GMDH model demonstrates proficiency in adaptive self-organization, automatic feature extraction, managing non-linear relationships, and interpretability, enhancing its effectiveness in capturing complex patterns in CO2 emission data. The observed decrease in performance for specific inputs during the forecasting process highlights the necessity for improving and adjusting the model and developing a detailed grasp of the dynamics of the variables involved. Notwithstanding these challenges, the study acknowledges the importance of CO2 emission forecasting for policymakers, industries, and environmentalists. It empowers them to make well-informed choices, implement measures to reduce harm, contribute to worldwide efforts to combat climate change and achieve emission reduction objectives. In essence, our research promotes a collective dedication to a future that is both environmentally friendly and resilient in the face of challenges.
Copyright (c) 2024 BASRI BADYALINA, Fatin Farazh Ya’acob, Rabiatul Munirah Alpandi, Nur Diana Zamani, Muhammad Zulqarnain Hakim Abd Jalal, Amir Imran Zainoddin https://creativecommons.org/licenses/by-nc-sa/4.0