Applied Information Technology And Computer Science
The Applied Information Technology and Computer Science (AITCS) is an open access and peer-reviewed periodicals published by the Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia. AITCS aims to provide an intellectual platform to disseminate knowledge. AITCS welcomes article submission of any original work and development in the the field of Information Technology and Computer Science that includes (but not limited to) Information Security, Software Engineering, Web Technology, Multimedia and Information Systems.
The Development of ASE Furniture: Mobile Based Furniture Shopping Application
Furniture shopping has evolved significantly with the rise in e-commerce, offering customers greater convenience and accessibility. Arif Sufian Enterprise, a furniture store located in Kuala Sungai Baru, Melaka, has been operating offline for over three years, selling items such as closets, carpets, sofas, and beds. However, the absence of an online platform limits its audience reach and customer engagement. To address these challenges, this project aims to develop an Android mobile application using Flutter that includes modules for user account creation, online purchasing, and a loyalty program to reward returning customers. The Firebase database manages product inventories and user data, ensuring real-time synchronization and scalability. Initial testing demonstrates improved customer engagement, higher satisfaction, and enhanced accessibility compared to the store’s offline operations. This project successfully transitions Arif Sufian Enterprise into the digital marketplace, expanding its reach and modernizing its sales processes, thereby positioning the store competitively within the furniture e-commerce industry.
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Neighbourly: A Mobile Application for Uniting Local Engagements in Bandar Springhill
The Bandar Springhill community, located between Port Dickson and Seremban, traditionally relied on unorganised platforms such as Facebook and WhatsApp groups to access local skills and services. This often resulted in inefficiencies and led residents to seek external resources, overlooking the talents available within their neighbourhood. The Neighbourly platform was developed to address this issue by facilitating structured community interaction and resource sharing. Adopting the Prototype Model, the application was designed and implemented using Android Studio and Flutter for the front end, with Firebase integrated as the real-time backend solution. The prototype features a Login and Registration, User Profile, Skill Listings, Chat, Review and Rating, Volunteering Events, and an Admin Dashboard accessible through unique login credentials. The Neighbourly platform aims to empower Bandar Springhill residents by improving access to local resources, encouraging collaboration, and fostering self-reliance. Ultimately, it seeks to contribute to building a more cohesive, sustainable, and connected neighbourhood.
Smart Autoplanter: Automatic Plant Cultivation System
This project aims to address the inefficiencies in cultivating plants, especially in urban areas. The Smart Autoplanter is a system that provides a way to automate plant cultivation, like watering and fertilization needs and plan harvest schedules. In addition, the system’s objective is to design and develop a working prototype and have it tested to meet the user’s expectation. The system’s modules manages the planter , gardening routine , harvest planning , custom plant cultivation and modular gardening . By implementing this system, the project aims to reduce the plants’ tending and nurturing period in urban settings, and enhance their cultivation while providing a way for users to learn along the way. The chosen methodology for this project is the Prototyping model, which includes iterative development, user feedback and continuous improvement. This project provides an innovative approach to urban gardening trend that is in line with rapidly evolving automation technologies.
A Phishing and Malware Link Detector Using Checkphish API
The Suspicious Link Detection Extension is a web-based tool designed to enhance online security by providing real-time URL safety checks to protect users from phishing scams, malware, and other potential internet threats. Developed with Node.js and integrated with the Checkphish API, the extension evaluates URLs based on various factors, including their structure, domain reputation, and other identifying characteristics. Unlike traditional URL-checking tools that rely on outdated databases or user-reported issues, this extension offers real- time analysis of links, ensuring that users receive the most up-to-date information about potential threats. The extension’s user-friendly interface is designed with non-technical users in mind, allowing anyone to easily input URLs and receive immediate feedback on whether the link is safe, suspicious, or potentially harmful. This makes it an ideal tool for individuals, educational institutions, and businesses concerned about cybersecurity, offering a simple and effective way to prevent users from visiting malicious websites. The tool aims to bridge the gap between complex cybersecurity measures and everyday internet users by providing an easy-to-use, real-time safety check, ensuring a moresecure browsing experience for everyone. By making security technology more accessible, this project strives to create a safer internet environment, particularly for those with limited technical knowledge.
Web extension tool,Spam comment detetction, Word filtering, Javascript,HTML,
Eye care is essential in overall health care, as our vision allows us to perform daily activities independently. It is important to get regular eye check-ups to maintain healthy eyesight. However, rising of digital devices causes people exposed to extensive screen time which can lead to progressive vision deterioration. Despite this problem, accessible tools for reducing screen-induced eye strain remain limited. This issue often results in neglecting eye strain indications due to insufficient awareness of eye care. Therefore, the EyeRis Shield Website is proposed to self-detect vision disorders and provide eye care tools. Prototyping methodology is implemented to develop this website. The prototype is built using the Windows platform via Visual Studio Code. The tested prototype results in each actor successfully linked with their respective module. This application is expected to serve as an eye health resource for early detection of eye conditions and foster healthy eye care habits.
MATH Mastery: Development of 2D Mathematics Learning Application for Matriculation Students
The MATH Mastery application solves fundamental issues encountered by Malaysian matriculation students when studying mathematics, such as fragmented tools and a lack of real time feedback. This study is to develop 2D mobile learning application adapted to the matriculation syllabus, develop it with gamified approach on the Android platform using Unity and C#. The approach used in the development was Multimedia Mobile Content Development (MMCD). Findings indicate that gamification and real-time feedback considerably improve engagement, learning efficiency, and satisfaction with the application. The study finds that MATH Mastery provides an integrated and engaging learning platform, with possible future enhancements such deeper chapter material, improved gamification components, and broader usability testing. The average score of respondents using the System Usability Scale (SUS) was 72.25% which falls in acceptable range. To improve learning outcomes and user engagement, future work will include cross-platform support, AI-driven hints, extended content modules, and extensive longitudinal research.
A Web-Based Pool Facility Booking Application For UTHM Sport Centre With Device-Based Authentication
UTHM's pool facility relies on a manual, counter-based booking and payment system using paper records, creating three critical challenges: lack of online booking capabilities, inefficient user record management affecting emergency response, and inadequate access control. The project aims to develop a digital platform with secure authentication, online booking, and two-tier administrative access. Following a six-phase methodology, from MoSCoW-based requirements gathering to post-implementation review, the system will implement user-friendly architecture, secure coding practices, and comprehensive testing protocols. The resulting platform will benefit the stakeholder by providing secure authentication for online payments, efficient booking management, improved emergency response capabilities, and enhanced reporting tools for management decision-making, effectively transitioning the facility from paper-based to digital operations.
SIS: Student Information System for SMKTMI with RBAC
Implementing information systems at educational institutions has several advantages, including increased security, better data accessibility and more effectiveness in sharing and managing important data. However, The Ministry of Education's system, which SMK Tunku Mahmood Iskandar (SMKTMI) currently uses to manage student, parent and teacher data has limited capability. In order to overcome these constraints, a web-based Student Information System (SIS) with Role-Based Access Control for SMKTMI is develop. Agile methodology is used and the system was constructed with PHP, HTML, CSS and MariaDB database. The system have modules for class scheduling, academic assessment, attendance tracking and discipline record. It supports Role Based Access Control for admin, teachers, students and parents with security features such as email verification, limited failed login attempt and password policy.
The Café Hopper Platform is a web-based solution designed to enhance the café discovery and booking experience for both customers and café owners. Developed using Agile methodologies, the platform offers a centralized hub for locating cafés that align with diverse consumer preferences, such as pet-friendliness or Wi-Fi availability, while promoting visibility for small, local establishments. The front end is built with HTML, CSS, and JavaScript to ensure an intuitive user interface, while the back-end leverages PHP and MySQL for secure data management, process integration, and user authentication. Key features include personalized café search, real-time booking, a payment gateway, and a unique review system. Integrated APIs support location-based search and advanced filtering, and the responsive design ensures usability across devices. Café owners can manage profiles, update information, and interact with customer feedback to boost engagement and reputation. Developed in a prototype scope using Visual Studio Code and XAMPP for the local environment, the platform’s modular architecture enhances scalability and maintainability. By streamlining the café search process and offering robust tools for customer-business interaction, the Café Hopper Platform fosters a thriving café culture and supports the growth of independent café entrepreneurs.
Employee Management System For SMK Ilhami Aikmel with Role-Based Access Control (RBAC)
Efficient management of employees is essential for the smooth operation of organization. Employee management at SMK Ilhami Aikmel currently relies on manual processes, causing inefficiencies and security risks. This study develops a web-based Employee Management System (EMS) with Role-Based Access Control (RBAC) to streamline staff management and secure data access. By utilizing Agile methodology, the system was designed with roles and sub-roles aligned to the school’s organizational hierarchy, ensuring precise RBAC. Testing through functional testing, security testing and user acceptance methods showed improved operational efficiency and enhanced security by restricting access based on user roles. The findings demonstrated significant improvements in operational efficiency and strengthened data security by enforcing the principle of least privilege. Future work could explore integrating additional modules and expanding the system for broader institutional use.
AR Moon Stellar Explorer: An Immersive Learning Tool for Year 5 Students
The integration of Augmented Reality (AR) in educational applications has garnered attention for its potential to engage students more effectively in Science learning. The AR Moon & Stellar Explorer application enhances Year 5 students' understanding of astronomy by providing interactive and immersive experiences centered on the phases of the moon and constellations. This project is particularly significant in addressing the challenges faced by Malaysian students transitioning from learning Science in their native languages to English-based curricula. By offering an AR-based English-learning environment, the application not only bridges this language gap but also fosters a deeper comprehension of complex astronomical phenomena. Developed using the Multimedia Mobile Content Development (MMCD) methodology, the application features interactive elements such as 3D models, AR sessions, and gamified quizzes, creating an engaging and dynamic learning environment that accommodates various learning styles and ensures students grasp both the scientific content and relevant English terminology. Targeting Year 5 students, beta testing revealed a positive satisfaction rate of 84.6%, confirming that the AR Moon & Stellar Explorer application effectively enhances learning outcomes and is well-received by users, despite some challenges with professional terminology.
RCARS: Residential College Accommodation Rental System for Student Housing Center
RCARS is a web-based Residential College Accommodation Rental System developed for the Student Housing Centre (PRP) of Universiti Tun Hussein Onn Malaysia (UTHM) to address challenges associated with manual accommodation application management. It streamlines the processing of applications, status monitoring, and payments through five main modules. Login and Registration manages user access, while Accommodation Application allows users to submit requests and receive updates. Admin Management oversees applications, packages, hostels, and generates related reports. Payment and Quotation automatically calculate fees and generate receipts, while Room Allocation and Management handles room availability and automate room assignments. Developed using Laravel, HTML, CSS, and JavaScript, RCARS emphasizes usability and operational efficiency. It adopts an incremental prototyping approach, allowing iterative testing and continuous improvement based on user feedback. User acceptance testing indicated high satisfaction in terms of usability, functionality, design, and reliability. By reducing administrative workload and improving overall user experience, RCARS significantly enhances the effectiveness and accessibility of UTHM’s residential accommodation management.
AI Video Detection using Convolutional Neural Networks
This project develops an Artificially Intelligent (AI) video detection and analysis tool by using Convolutional Neural Network (CNN). The tool is based on an effective Python architecture that uses OpenCV and specially trained YOLOv8 CNN models. Its three main features include object detection for security monitoring, age estimation with demographic analysis, and facial expression recognition for eight emotional states (Anger, Contempt, Disgust, Fear, Happy, Neutral, Sad, and Surprise). The tool offers hands-on experience with computer vision techniques and security surveillance through real-time video processing with overlay annotations and analytics dashboards. The trained model achieves 83.6% accuracy in facial expression detection with real-time processing capabilities for comprehensive video analysis. This CNN-based AI video detection tool was created as a learning platform for students pursuing computer vision and artificial intelligence. It combines theoretical understanding with hands-on application of convolutional neural network technologies for practical security, surveillance uses, and digital forensic image analysis for investigative purposes.
Student E-hailing Application with Multifactor Authentication
Transportation is an essential aspect of university students’ daily lives. However, students without personal vehicles face significant challenges, relying on public transportation or other available alternatives such as ride-hailing and walking. The Student E-Hailing Application with Multi-Factor Authentication addresses transportation challenges faced by university students by ensuring all users are verified as legitimate students, ensuring the safety and trust of students. Developed using Flutter and Firebase, the application employs Agile methodology for iterative development and integrates Multi-Factor Authentication for enhanced security. The implemented authentication methods are password, student email verification and biometric authentication such as fingerprint. Key findings indicate the system effectively creates a trusted network, addressing issues such as unreliable transportation and unverified drivers.
Sistem Cadangan Produk Mekap dan E-Dagang Berasaskan Web Brew Beauty
Brew Beauty dibangunkan bagi mengatasi kekangan yang dihadapi oleh kedai Brew Beauty di Parit Raja, termasuk ketiadaan platform e-dagang dan kaedah pengurusan stok yang masih manual. Keadaan ini menyukarkan pelanggan untuk mencari produk mekap yang sesuai dan menyulitkan pemilik dalam mengurus inventori dengan cekap. Kajian ini membangunkan sebuah sistem yang merangkumi enjin cadangan hibrid (berasaskan kandungan dan peraturan), pengurusan inventori secara masa nyata, modul pembayaran menggunakan imbasan kod QR, serta laporan analitik, demi meningkatkan pengalaman pelanggan dan kelancaran operasi kedai. Sistem ini dibina menggunakan rangka kerja Python/Django dan dinilai melalui ujian unit serta Ujian Penerimaan Pengguna (UAT) yang melibatkan sepuluh responden. Hasil penilaian menunjukkan kadar kelulusan ujian unit sebanyak 100% dan tahap kepuasan pengguna sekurang-kurangnya 4 daripada 5 bintang, di samping peningkatan ketara dalam aliran pembelian dan ketepatan cadangan produk.
PhishBlocker: Phishing Detection System based on Uniform Resource Locator (URL) using Hybrid Approach
Phishing attacks remain a significant threat, emphasizing the need for effective detection systems. This study presents PhishBlocker, a URL-based Phishing Detection System using an integrated approach combining Support Vector Machine (SVM) with rule-based scoring to distinguish phishing URLs from legitimate ones. The system uses a balanced dataset of 60,000 URLs that consists of 30,000 phishing, 30,000 legitimate URLs, cleaned and analyzed with 22 features like domain age, ssl validity, redirection depth and phishing-related keywords. Implementing Object-Oriented Analysis and Design (OOAD), PhishBlocker uses a consensus scoring approach, integrating SVM and rule-based scores. The dataset is split 80:20 for training and testing, with n-fold cross-validation for model evaluation. The system is developed in Python with Flask, Scikit-learn and Chart.js, the system achieved 93% accuracy from training and testing with the balanced dataset. Future work should integrate deep learning and real-time adaptive training to enhance detection, benefiting organizations, cybersecurity professionals, and end-users with improved phishing defenses and reduced false positives.
Development of Virtual Reality Application on Pineapple Farm Exploration: PinExplore VR
Virtual reality technology is now commonly employed to replicate the actual world in several businesses. Virtual reality technology is typically utilised for both agricultural education and enjoyment. Nonetheless, young farmers who wish to learn how to grow pineapples frequently employ old methods. Furthermore, by not utilising the available technologies for training, the learning approach is less successful. Thus, PinExplore VR, an agricultural exploration software that fully utilises virtual reality technology, will be created for the Windows operating system. Target users for this project are public aged 20 to 30 years old. The PinExplore VR application was developed using the Prototyping model methodology. The user should find this application entertaining and useful in imagining risk-free pineapple cultivation. The SUS approach will be used for testing and evaluation in order to determine whether usability is acceptable. The Acceptability Ranges of the average score is 70.63, which in the “acceptable” range and “Good” is the adjective rating. In the nutshell, the target users are satisfies with the application.
MindCare: Development of Mobile Application on Mental Health Monitoring for Pusat Kesihatan Universiti UTHM
Mental health is essential, but many avoid addressing it due to stigma, low awareness, and limited support access. The UTHM Health Centre relies on time-consuming, traditional in-person processes and lacks an efficient student mental health tracking method, while existing apps often lack personalized and holistic features. The project addresses the problem of inefficient mental health monitoring, which often causes delays in intervention, undetected emotional distress, and a decline in student well-being. This project uses Flutter to develop a cross-platform mobile app addressing these challenges and the app includes mood tracking, journaling, personalized self-care suggestions, and mental health resources to help students monitor and enhance their well-being. The application has been designed for the UTHM Health Centre to replace manual mental health tracking with a digital solution that improves monitoring and support. Therefore, it offers insights into student well-being, enabling better resource allocation, early interventions, and proactive mental health practices.
Electronic Hasta La Vista (e-HLV): Student Assessment System for Finishing School
The Electronic Hasta La Vista (e-HLV) Student Assessment System is developed to streamline the assessment process for students, educators, and coordinators in higher education institutions, particularly Universiti Teknologi MARA (UiTM). This system addresses inefficiencies in the current manual processes, such as time-consuming data handling, errors in mark entry, and delays in feedback. The system incorporates features like secure login, automated grading, real-time feedback, and report generation to improve assessment management. The Prototyping methodology is employed, involving iterative development to refine the system based on user feedback. The implementation of the e-HLV System for a web-based platform is done using Visual Studio Code. Based on the results of the testing phase the system proves effective in automating the marking process, reducing errors, and enhancing overall efficiency for both students and educators.
Development of a Virtual Reality Baking Lab Application for Bakery Students at UTHM : KitchenLab
The Bakery and Pastry Arts course at UTHM is designed to equip students with essential baking knowledge and hands-on skills through practical modules and kitchen-based training. However, traditional methods face challenges such as high resource consumption, time constraints, and limited practice opportunities. To overcome these issues, KitchenLab was developed as an innovative Virtual Reality (VR) application tailored for UTHM bakery students. Guided by SME Dr. Siti Hajar Binti Zakariah, the app follows the TRES-D methodology, which emphasizes iterative evaluation, design, development, and testing. KitchenLab simulates critical baking stages, including preparation, proofing, and baking, offering an immersive and efficient learning alternative. To assess usability, the System Usability Scale (SUS) was administered to 20 UTHM bakery students. The application achieved an average SUS score of 73.75, indicating above-average usability and positive user acceptance among its target users.
UTHM Student Attendance System Using Blockchain Technology
The UTHM Student Attendance System using Blockchain Technology is designed to enhance the efficiency, data integrity, and traceability of student attendance records. Traditional attendance systems often face issues such as data manipulation and inaccuracies. By integrating blockchain technology, the system ensures immutable and transparent attendance records. The project employs the Prototyping Model, which facilitates iterative development through planning, analysis, design, implementation, and testing phases. The system's core is built using PHP, JavaScript, and Ethereum smart contracts to securely log attendance data. The system is implemented at Universiti Tun Hussein Onn Malaysia (UTHM) to replace conventional methods. The outcome of this system is a robust platform that mitigates fraudulent records, improves data accuracy, and streamlines administrative tasks, benefiting both students and lecturers.
An Enhanced Feature Extraction using Chebyshev Wavelet Filter for Iris Recognition System
This research explores an enhanced feature extraction method for iris recognition, addressing the limitations of existing techniques like Gabor filters and wavelet transforms, which struggle with noise and image variations in non-ideal conditions. The objective of this research is to design and evaluate a feature extraction method using Chebyshev wavelet filter, testing its performance in terms of False Acceptance Rate and False Rejection Rate, and assessing its effectiveness in handling variations. The study utilizes three publicly available datasets (CASIA, MMU, and UBIRIS), the methodology involves preprocessing iris images from the datasets and applying the Chebyshev wavelet filter for feature extraction and employing support vector machine for classification. This proposed system aims to improve recognition accuracy and robustness in non-ideal conditions. The expected outcome is to achieve higher accuracy rates and lower FAR and FRR compared to traditional methods. This research contributes to the development of more efficient iris recognition systems.
A Random Forest and Logistic Regression Based Tool for Credit Card Fraud Detection
Detecting credit card fraud is an important issue in financial transactions since it could result in large financial losses and data breaches. However, traditional rule-based systems frequently struggle with imbalanced datasets and are unable to adapt to changing fraud strategies. This project suggests a machine learning-based fraud detection tool that identifies transactions as either valid or fraudulent by using Random Forest and Logistic Regression. The Synthetic Minority Oversampling Technique (SMOTE) is employed to handle data imbalance and enhance model accuracy. Implemented as a web-based platform with Flask, the tool allows fraud analysts in banking and financial institutions to upload transaction files, analyse results, and visualize fraud patterns. The tool is expected to address the limitations of traditional methods and offer an approach for securing digital financial systems by decreasing false positives and improve fraud detection accuracy.
RETINA: Network Intrusion Detection System using Machine Learning Approach
In today's digital age, protecting networks from cyberattacks is crucial because it pose significant risks to sensitive data, financial assets and organizational reputation. However, traditional Network Intrusion Detection Systems (NIDS) often face challenges such as inefficiency, limited accuracy, and difficulty handling real-time data. To address these issues, we proposed a Real Time Anomaly (RETINA) system using machine learning approach. RETINA will be focusing on real-time packet analysis and threat classification to detect Dos attack and brute force attack. The development follows the Object-Oriented Analysis and Design (OOAD) methodology. The project employs XGBoost algorithm and dataset from CICIDS 2017 for threat classification, Scapy library for real-time packet capture, and a web-based interface for monitoring and visualization. The project primarily benefits network administrators by enabling them to identify and respond to security threats proactively. The outcome of this project will highlight the potential of intelligent algorithms in advancing intrusion detection systems. The final developed system could detect Denial of Service (DoS) and Brute Force Attack and significantly low 0.07% False Positive Rate.
MUHAMMAD ZAINURAIN BIN MOHD ZAIN @ MOHD FAHMI MOHD ZAIN
Swimming Facilities Management System for Universiti Tun Hussien Onn Malaysia Sport Centre with Two-Factor Authentication
The Swimming Facilities Management System for Universiti Tun Hussein Onn Malaysia (UTHM) Sports Centre with Two-Factor Authentication was developed to address inefficiencies in the management of swimming pool facilities and improve the overall operations of the Sports Centre. The existing manual process such as an inefficient booking process for swimming pool activities, a poor data management for users and an inefficient payment process for walk-in users, have proven to be time-consuming and prone to errors. To resolve these issues, the project adopts the Waterfall methodology, which provides a structured, sequential approach with a focus on clear documentation and well-defined requirements at each stage of development. The project aims to design a proposed system by implementing Role-Based Access Control, developing secure management system with Two-Factor Authentication and testing the functionality of the developed system. The expected outcome is a user friendly interface that allows students, staff, and visitors to efficiently manage bookings, process payments, and access services, while securely handling user data.
TryMeOut: A Vulnerability Web Application for Security Students Learning
TryMeOut is a web-based platform developed to support cybersecurity students in gaining practical, hands-on experience with common web application vulnerabilities. This platform allows students to safely explore and exploit real-world vulnerabilities such as SQL injection, Cross-Site Scripting (XSS), and Command Injection in a secure, controlled environment. The system features a progression of interactive challenges, starting from basic scenarios and advancing to more complex ones. This structure helps students build their skills gradually, reinforcing core concepts while encouraging exploration and problem-solving. Each vulnerability category includes multiple levels that simulate realistic attacks, giving students valuable experience in recognizing, exploiting, and understanding the impacts of these threats. Targeted primarily at bachelor’s degree students in the Information Security program at Universiti Tun Hussein Onn Malaysia (UTHM), the platform aims to offer a user-friendly, educational space that bridges the gap between theory and real-world application. This project is developed using the Waterfall Model methodology, which follows a clear, linear process from planning and analysis to design, implementation and testing.
A Mobile Game-Based Application for Learning Collective Nouns of Animals: Nounimals
Game-based learning enhances engagement by combining educational content with interactive play. Traditional methods of teaching collective nouns for animals often lack interactivity, and existing apps with static visuals and text-based quizzes make it difficult for primary school students to learn this knowledge. Hence, Nounimals is a mobile application that uses game-based learning technology has been developed by using a Multimedia Mobile Content Development methodology. The app targets primary school students, offering 2D visualizations, gamified quizzes, and real-time feedback to make learning collective nouns more engaging. The System Usability Scale (SUS) was used to evaluate user acceptance, resulting in a positive usability score of 71.5, which is above the average benchmark of 68 and indicates good usability and user satisfaction. Thus, Nounimals are suitable to be implemented in learning collective nouns of animals is expected.
AI-based Intrusion Detection System (IDS) using Behaviour Analysis
A rise in cyber threats, such as Denial of Service (DoS) attacks, has highlighted the limitations of traditional Intrusion Detection Systems (IDS) in Malaysia’s cyberspace. Existing IDS face difficulties in detecting new threats due to reliance on signature databases and high false positive rates. To address these issues, an AI-based IDS utilizing Long Short-Term Memory (LSTM) networks and behavior analysis techniques is proposed. LSTM improves anomaly detection by learning traffic patterns over time, while behavior analysis enhances accuracy by focusing on deviations from normal network behavior. The tool consists of three modules: monitoring, anomaly detection and user interface. The AI-based IDS tool aims to provide real-time threat detection for individuals and organizations. The expected outcome is a reliable IDS with improved accuracy and reduced false positives, promoting safer network environments.
Sistem Perancangan Pelajar FSKTM di UTHM
Pelajar Fakulti Sains Komputer dan Teknologi Maklumat (FSKTM) di Universiti Tun Hussein Onn Malaysia (UTHM) dikenal pasti menghadapi masalah dalam pengurusan masa, penghantaran tugasan, dan penyusunan jadual waktu yang sistematik. Pembangunan sistem Permasalahan ini boleh memberi kesan kepada prestasi akademik pelajar. Oleh itu, sistem perancangan pelajar khusus untuk pelajar FSKTM, UTHM dibangunkan bertujuan untuk menyelesaikan isu-isu yang dikenal pasti tersebut. Sistem ini dibangunkan menggunakan kaedah model prototaip, di mana ia mempunyai lima fasa: perancangan, analisis, reka bentuk, pelaksanaan, dan pengujian. Bahasa pengaturcaraan yang digunakan semasa proses pembangunan sistem adalah PHP, JavaScript, HTML dan CSS berdasarkan reka bentuk (ERD), (DFD) dan antara muka pengguna (UI). Sistem ini direka dengan ciri-ciri yang dikenal pasti dapat memenuhi keperluan pelajar. Untuk menilai tahap penerimaan dan keberkesanan sistem, Ujian Penerimaan Pengguna (UAT) telah dijalankan melibatkan sebilangan pelajar FSKTM. Hasil daripada ujian tersebut menunjukkan bahawa sistem ini berfungsi dengan baik serta mampu memenuhi keperluan asas pelajar dalam pengurusan akademik harian. Kesimpulannya, sistem ini berpotensi menjadi alat yang signifikan dalam membantu pelajar merancang masa dengan lebih berkesan. Penambahbaikan lanjut akan dilaksanakan pada masa hadapan bagi memperluaskan fungsi dan meningkatkan keberkesanan sistem berdasarkan keperluan pengguna.
Fakulti Sains Komputer dan Teknologi Maklumat (FSKTM)
Universiti Tun Hussein Onn Malaysia (UTHM)
Unsafe Condition and Unsafe Act (UCUA) Reporting System For Johor Port with OTP Authentication
The Johor Port Unsafe Condition and Unsafe Act (UCUA) Reporting System handles the issues of managing safety reports, which are currently handled via paper forms and limited online submissions, resulting in delays and increased safety concerns. The goal of this project is to create a web-based UCUA Reporting System applying the Laravel framework, which will streamline the reporting and tracking processes for port personnel and the Health, Safety, Security, and Environment (HSSE) department. The key components like incident reporting, compliance tracking, and notifications are all part of the system, which was created using structured web application approach. The system incorporates important security features like input validation, role-based access control, user authentication, and encrypted data processing to guarantee safe and dependable operations. By improving efficiency, accountability, security, and data management, this system's operation enables quicker reactions to safety concerns and better regulatory compliance. It is expected that future advancements like advanced analytics integration and mobile accessibility would enhance Johor Port's reporting system even more.