Applied Mathematics and Computational Intelligence (AMCI)

Boundary Layer Flow of Dusty Ferrofluid: A Comparative Analysis of Stagnation Flow Influence

Cik Siti Hajar Abdulah — 2024-11-07

This research examines the characteristics of the boundary layer in the occurrence of dust particles within the ferrofluid boundary layer, aiming to understand the impact of stagnation flow or without stagnation flow in such systems. For this purpose, ferroparticles, namely magnetite (Fe3O4), are taken into consideration with kerosene and water as base fluids. The governing partial differential equations of the problem under consideration are converted into ordinary differential equations (ODEs) through the utilization of similarity transformations. Here, the equations obtained are then numerically solved utilizing MATLAB's built-in bvp4c solver. Moreover, the parameters’ effects, namely the dust particle loading, volume fraction of ferroparticles, and Eckert number to the flow with and without stagnation flow are computed and shown through tables and graphs. The findings indicate that the skin friction coefficient values for the stagnation-point flow are higher than those without stagnation-point flow. The Eckert number increases temperature profiles for both flows but more prominent in the flow without stagnation-point.

Mapping the Research Landscape of Ordinary Differential Equations through Bibliometric Analysis

Amirul Syameer Abd Rahman — 2024-11-07

Ordinary Differential Equations (ODEs) are a fundamental field used for mathematical modelling in wide-ranging applications. This research visually represents the research landscape of ODEs by utilizing bibliometric analysis and social network analysis. We analysed 1,849 documents related to topic developments, patterns in publications, and collaborative networks spanning the years 2019 to 2024. Consequently, numerous papers have been published by authors from the United States, China, and Russia, where research activity is significantly focused. The analysis identifies the articles with the highest citation rates, as well as the important authors and universities that are at the centre of publishing on ODEs. Furthermore, we display the collaborative network of the research group and countries using the VOSviewer application. In conclusion, the study highlights the current state and progress of ODE research by identifying recent developments and intriguing topics for future exploration. This paper serves as a valuable reference for researchers seeking to understand the impact and progress of ODE investigations within the broader mathematical domain.

An Educational Wildlife Game-based Learning Application for Young Learners Using Augmented Reality

Nik Nahdiya Nik Kamaruzaman — 2024-11-07

These digital days, the learning curve in the educational sector is changing progressively because of technological advancements and societal demands. Technology integration, particularly, provides the ability to engage in diverse learning platforms, which then expose the learners to an immersive learning experience. This study introduced augmented reality (AR) game-based learning mobile application to young learners in exploring wildlife conservation. However, the challenge in mixing fun gameplay and essential wildlife education to foster young learner's interest in wildlife conservation can be tough. In capturing the attention of young learners, the project aims to create a captivating wildlife game application that combines education with entertainment. This project employs a prototyping method, allowing for iterative development and testing of the AR game application to ensure its effectiveness in delivering educational content. The application incorporates interactive elements such as 3D models of wildlife with vocal features and quizzes elements. Findings reveal that the application facilitated the refinement of game mechanics and educational content based on user feedback, leading to an engaging and educational final product. The results emphasize the success of the approach is not only capturing young learner's interest but also increasing their knowledge and awareness of wildlife conservation. In the future, the incorporation of other elements such as leaderboard, badges and rewards have the potential to stimulate young learners’ motivation to actively participate in the learning program.

Data Visualization of Student Academic Performance Analysis

Nur Farah Amira Shahidan — 2024-11-07

Understanding and enhancing student academic performance has become increasingly crucial, yet educators often face data overload, making identifying and prioritizing factors influencing student performance difficult. This study seeks to create a comprehensive system for visualizing and analysing student academic performance. The research follows the waterfall model, with clearly defined phases to ensure an organized and complete development process. The study's main objectives include determining the requirements and techniques to analyse student academic performance and developing and designing a data visualization dashboard using Microsoft Power BI. The final phase consists of evaluating of the student performance dashboard using the Technology Acceptance Model (TAM). A total of 35 respondents was randomly chosen for evaluation and hands-on sessions. The dimensions encompassed Perceived Ease of Use, Perceived Usefulness, Attitude towards Using, and Behavioural Intention. The Attitude of Using received the highest mean score of 4.39, closely followed by Behavioural Intention with a score of 4.38. The results indicate that the participants have a high level of satisfaction with using the dashboard, considering it advantageous and indicating a desire for future implementation. Finally, the project exhibits potential for further advancement, encompassing predictive analytics and tailored learning recommendations, aiming to provide even more precise and actionable insights into student performance.

Leveraging Gamification in Science Learning for Secondary Students

Nurtihah Mohamed Noor — 2024-11-07

This project aims to study the usefulness of incorporating gamification for science learning, for secondary school students. Ever since, the Science subject has been a hassle to the students, as well as the teachers. Therefore, a web-based system with gamification has been proposed. The waterfall model was chosen as the project's methodology, which consists of planning, analysis, design, implementation, testing, and documentation phases. Firebase was used as the cloud database to ease data storage and analysis. The selection was made to ensure the data from interactive activities such as watching films and doing exercises was securely gathered and used. Students earned points, badges, and were ranked as they performed assignments, adding a competitive element to the learning experience. A usability test was carried out to assess the success of the gamified learning platform using PSSUQ (Post-Study System Usability Questionnaire). The survey participants were chosen randomly from a group of high school students and teachers. After using the gamified website, they were asked to submit feedback by answering 16 constructed questions. Positive feedback was gathered from the survey, as most of the questions recorded mean values between 4.0 and 4.5. Hopefully, this study will provide further information regarding the effectiveness of gamification in learning, particularly in science learning for secondary students.

Exploring Diversity and Abundance of Stingless Bee using Clustering Approach

Nur Maziah Jalilah Jamil — 2024-11-07

Stingless bees are paramount in food chain as they are important pollinators of field crops. Recent studies revealed that these bees are seriously threatened by climate change and rapid urbanization across the world. It is thus important to study the relationship between the stingless bee’s diversity and the characteristics of the locations they inhibit. At the same time, clustering algorithms is a powerful machine learning approach in exploring unsupervised data. Consequently, this study aims to explore the stingless bee diversity in Malaysia through hierarchical, k-means and DBSCAN clustering. The dataset of this study consists of individual stingless bees collected from 12 locations. It comprises 14 environmental features, 3 physical characteristics, 35 species count, 12 genera counts and 3 diversity-and-abundance weights. A four-stage methodology is employed in the study. The results show that DBSCAN effectively groups data into clusters that are well-defined, but the results are less informative. In contrast, hierarchical and k-means clustering are found producing results that provide clearer insights, with hierarchical clustering delivering notably richer results.

Comparison of The Trapezoidal and Adam Bashforth Approaches in The Lotka-Volterra Prey-Predator Dynamics

Nor Solehah Sanik — 2024-11-07

This study primarily focuses on comparing the numerical methods of the Adams-Bashforth and Trapezoidal methods with the exact solution for solving the Lotka-Volterra prey-predator model. These methods are evaluated for their ability to reliably and accurately solve the non-linearity of the model. Based on the results, both methods offer precise solutions, with the Adams-Bashforth method providing a more accurate approximation for short-term predictions and the Trapezoidal method demonstrating better stability for long-term simulations. The study utilizes data from lynx-rabbit and bat-moth interactions to assess the performance of these methods using software tools. For both models, the short-term predictions align closely with observed data, while long-term stability analyses reveal the strengths of the Trapezoidal method. The equilibrium and stability analyses offer critical insights into the long-term behavior and stability of the system. The predator population trails behind the prey population: a rise in prey numbers is followed by a delayed increase in predator numbers as predators consume more prey. The phase portraits show the regularity of these oscillations. The curves move counterclockwise: prey numbers increase when predator numbers are at their lowest, and prey numbers decrease at their highest. These insights are essential for understanding and predicting the dynamics of predator-prey interactions and have significant implications for ecological modeling and conservation strategies.

Forecasting of Menstruation using a Calendar-based Method based on a Web Application

Aida Yasmin Zainal Abidin — 2024-11-07

Accurately predicting menstrual dates is valuable for women, yet it poses a significant challenge, particularly for those with irregular cycles. This study introduces a web application that utilises a calendar-based method to predict upcoming menstrual dates while offering additional features such as tracking past periods, logging symptoms, and providing personalised health advice. Using the software development life cycle approach, the critical contribution of this work is the development of a user-friendly tool that not only aids in menstrual tracking but also highlights the limitations of calendar-based predictions, especially for women with irregular cycles. Our findings suggest that while the method provides accurate predictions for women with regular cycles, it is less reliable for those with irregular cycles due to its dependence on a fixed cycle length range. This study underscores the need for more adaptive models to improve prediction accuracy for a broader population.

An Assessment Mechanism for Integrated Software Sustainability Evaluation Model via Evaluation Theory

Ruzita Ahmad — 2024-11-07

Evaluation of software sustainability aids in decision-maker’s identification of the specific actions needed to guarantee sustainability for current and future generations. The prior approach to assessment focused on how the business environment was changing and using the high-quality software sustainability evaluation model (SSEM) affected those changes. Numerous well-established quality models, concepts, and understandings impacted on SSEM trends. These act as frameworks for developing software evaluations, the outcomes of which are applied to the assessment of generic software procedures. Therefore, this research aimed to use Evaluation Theory (ET) to create an assessment mechanism for an integrated Software Sustainability Evaluation Model (i-SSEM). This model encompasses evaluation criteria, targets, assessment processes, data-gathering techniques, synthesis techniques, and yardsticks. Nine criteria are presented in this study to evaluate software sustainability encompassing functional adequacy, dependability, performance efficiency, usability, security, compatibility, maintainability, portability, and impactibility. The use of the Quality Function Deployment (QFD) methodology, effectively classifies the recommended criteria into sustainable dimensions. A Goal Question Metric (GQM) is used to establish the software criteria by precisely specifying the aim, perspectives, and viewpoints of an evaluation of the sustainability aspects. By highlighting the unique evaluation mechanism for software products and processes and utilizing both quantitative and qualitative measurement techniques, this model improves the current SSEM.

Post-Pandemic Financial Distress Analysis: A Study of Retailer and Tourism Companies Listed in Bursa Malaysia Using the Grover Model

Sharmila Karim — 2024-11-07

A corporation enters financial distress when its cash flows are insufficient to cover its debts to stakeholders, both financial and non-financial. When the Coronavirus Disease 2019 (COVID-19) pandemic struck the world and caused lockdowns that impacted many businesses, particularly those in the tourism and retail industries, the likelihood of financial distress increased. Thus, the Grover model is used to determine and analyse the financial distress prediction in retail and tourist companies listed on Bursa Malaysia. The Grover model categorises companies as financially distressed with a G-Score equal to or less than -0.02. Meanwhile, the G-Score for companies in the safe zone is equal to or greater than 0.01. Four companies were chosen, and a sample of data was collected from 2017 to 2021. The findings showed that during the COVID-19 pandemic from 2020 to 2021, three companies were under financial distress, especially those in the tourism and hospitality sectors. Meanwhile, retailer companies, especially those in food manufacturing, were not affected by this pandemic.