UTAR Institutional Repository (Universiti Tunku Abdul Rahman)
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Factors in influencing the purchase intention towards skincare products among Malaysian Muslim
Get PDFSkincare products have become essential daily. More people become concerned about the ingredients and the harmful effects when using skincare products. Malay accounts for most of the population in Malaysia, who are generally Muslims. As Muslims, they need to ensure the use of Halal products that are free from prohibited ingredients according to Islamic principles. Therefore, this study investigates the factors influencing the purchase intention of skincare products among Malaysian Muslims by extending the Theory of Source Credibility (SCT). The research incorporates five key constructs–attractiveness, trustworthiness, expertise, and religious commitment–to assess their effect on purchase intention. Data were gathered through a structured questionnaire distributed to Malaysian Muslim respondents aged 18 years and above. Statistical Package for the Social Sciences (SPSS) was utilized to analyse a total of 299 valid responses. Findings revealed that attractiveness, trustworthiness, and expertise significantly influence purchase intention, whereas religious commitment did not significantly affect. This study contributes to academic literature by expanding the SCT framework and offers practical implications for marketers and policymakers aiming to implement for future skincare to boost sales in the Malaysian Muslim market. Recommendations for future research and industry practices are also discussed to further enhance the offering of halal skincare products for Malaysian Muslims. Keywords: Skincare; Purchase Intention; Muslim; Malaysia; Theory of Source Credibility; HALAL Subject Area: HF5410-5417.5 Marketing. Distribution of product
A machine learning approach to tourism recommendations system
Get PDFThis project aims to develop a tourism attractions recommendation system by integrating machine learning recommendation algorithms. The main problem encountered when developing a powerful recommendation system is cold start problem, data sparsity and scalability problems. Cold start problem occurs when there is insufficient data about new users, new items or both. Data sparsity is a situation where there exists null value in the dataset, making it difficult to make predictions. Scalability problems arise when the system struggles to handle large volumes of data or a growing number of users and items. To overcome this problem, this project implements machine learning algorithms with collaborative filtering, content-based filtering and hybrid filtering approaches. Algorithms like Singular Value Decomposition, K-Nearest Neighbor and Co-clustering will be compared in this project. Model with the highest accuracy will be integrated into a tourism recommendation mobile application. A high portability and mobility mobile application will be developed by using React Native, and the dataset used in developing will be obtained from Google API. By developing this powerful recommendation system, travelers, tour guides and tourism agents will benefit by reducing their massive workload on planning trip itinerary
Mobile indoor navigation with object recognition for visually impaired
Get PDFNavigation is an important aspect in daily life, but visually impaired individuals might struggle
to navigate by themselves safely and independently. Nowadays, the advancement of mobile
solutions with artificial intelligence (AI) and computer vision (CV) technology has encouraged
the development of many innovative solutions to solve problems. In this project, a standalone
mobile application called Visiovigate is developed for indoor navigation assistance of the
visually impaired communities. It is designed to support visually impaired individuals by
integrating real-time object recognition, and indoor navigation using mobile sensors. Existing
assistive technologies often lack comprehensive indoor navigation abilities or are reliant on
expensive hardware. It might limit their accessibility and effectiveness. Thus, Visiovigate
addresses these gaps by leveraging deep learning and computer vision techniques by using the
You Only Look Once (YOLO) model for efficient object detection on mobile devices and
utilizing the mobile pedestrian dead reckoning mobile sensors like magnetometer and
accelerometer for indoor navigation without relying on global positioning system (GPS) and
internet connection. The application will also offer real-time audio and haptic feedback for
ensuring the visually impaired users receive immediate environmental awareness and
directional guidance. Therefore, this mobile application is best to use with a traditional solution
like cane that will further increase efficiency as this application can inform users about the
incoming obstacles that are not reachable by the traditional solution. This system operates
entirely on standard mobile sensors which have been commonly built into smartphones
nowadays. It aims to run in a stable condition at any mobile device without internet connection.
Hence, this project also will provide a more cost-effective and accessible solution that enhances
the safety and independence of its users in indoor environments
Fundamental stock analysis with LLMs and qualitative data: Development of ontology-grounded, graph-based RAG with text-to-Cypher retrieval for Malaysian listed companies
Get PDFFundamental analysis is essential for retail investors pursuing long-term investment, as
a company’s profitability ultimately drives its intrinsic value. At its core, fundamental
analysis relies on deriving implicit insights—such as operational resilience, governance
quality, or future growth potential—from explicit data, including financial disclosures
and corporate announcements. Retail investors, however, often lack the expertise,
resources, and analytical experience required to perform such analysis effectively. To
address this challenge, this study proposes a corporate insight derivation module
powered by Large Language Models (LLMs) that systematically transforms explicit
corporate disclosures into actionable implicit insights. The module employs a novel
ontology-grounded, graph-based Retrieval-Augmented Generation (RAG) pipeline
with text-to-Cypher retrieval. It comprises three sub-modules: (i) an Automated
Ontology Construction Module, which formalises domain-specific entities and their
relationships; (ii) a Graph Construction Module, which integrates heterogeneous
corporate data into a coherent knowledge graph capable of multi-hop reasoning; and
(iii) a Text-to-Cypher Retrieval Module, enabling natural language queries to access the
knowledge graph efficiently. The system leverages disclosures from five ACE Market
listed technology companies in Bursa Malaysia as a proof-of-concept. Evaluation
results demonstrate that the proposed pipeline successfully derives implicit insights,
with the Entity Deduplication process achieving a maximum deduplication rate of
73.0% and an overall rate of 66.5%, producing a compact and coherent knowledge
graph. Despite limitations in ontology scalability, dynamic adaptability, and prompt
robustness, the pipeline establishes a strong foundation for further refinement. The
proposed module holds potential as a practical tool for retail investors, supporting more
informed and rational decision-making by bridging the gap between explicit corporate
data and implicit investment insights
Compact tag antenna for metal-mountable applications in the UHF RFID passbands
Get PDFThis report presents the theoretical background, methodology, configuration of the proposed tag antenna, performance analysis and challenges encountered in developing the tag antenna. The aim is to design a compact and high performance metal mountable tag antenna for omnidirectional radiation
applications in the UHF RFID passbands. This project focuses on patch antenna structure that incorporates zeroth-order resonance (ZOR) principles to enhance performance while maintaining a compact form factor.
The study investigates the fundamental concepts of RFID systems and the impact of metal surfaces on antenna performance, as well as various approaches to overcome these challenges. Through a series of simulations using CST Studio Suite, design iterations were conducted to optimize the
antenna’s radiation pattern, gain, and impedance matching.
Overall, a compact UHF RFID tag antenna based on zeroth-order
resonance (ZOR) is proposed for on-metal omnidirectional tag design. The proposed tag antenna consists of two identical patches, which are placed in the antipodal arrangement. Each patch is connected to the ground by a pair of elongated shorting stubs as well as a pair of open-ended side stubs. This structure can generate sufficient antenna impedance for achieving good conjugate matching, despite having a miniature size of 0.0824λ × 0.0824λ × 0.0098 λ (or 27 mm × 27 mm × 3.2 mm). A tag prototype has been fabricated, and achieves a constant read range of ~9.8 m (4 W EIRP) in all azimuthal
directions with 4W EIRP when mounted on metal.
Keywords: UHF RFID tag; patch antenna; omnidirectional; on-metal; zeroth�order resonance
Subject Area: TK5101-6720 Telecommunicatio
Assessing the mechanical and microstructural properties of concrete with electric arc furnace slag replacement at 60%, 75%, and 90%
Get PDFNowadays, reusing the industrial by-products by aiming on sustainable objectives has risen as a important move in reducing the environmental impact by construction field. The objective of this study is to determine the mechanical
properties which is compressive strength through evaluating the microstructural properties of elemental and chemical compound composition of concrete with EAF slag replacement for natural fine aggregates at different ratios of 60%, 75%
and 90% for acrossing three particle size ranges (R1: 0.8 to 2.36 mm, R2: 2.36 to 4.75 mm and R3: 4.75 to 6.30 mm). Optimal replacement ratio which could provide optimum replacement ratio is also being determined. A total of 30
concrete samples were prepared and tested by using 5 tests which including of Compressive Strength Test, Scanning Electron Microscopy (SEM) Test, Energy Dispersive X-ray Spectroscopy (EDX) Test, X-ray Diffraction (XRD) Test and
Thermogravimetric Analysis (TGA) Test. The Compressive Strength Test shows that all EAF slag mixes concrete samples outperformed the control sample with the highest strength of 54.75 MPa. SEM Test had showed visibility of hydration products such as Ettringite, Portlandite and C-S-H gel in the
microstructural of concrete samples casted. EDX Test indicated existence of several elements but Calcium and Silicon as the elemental composition which contributes to affect the compressive strength. Results of XRD Test validated the presence of compounds such as Ca(OH)2, CaCO3, SiO2 and CaO and suggest that Ca(OH)2 and CaCO3 could contribute to affect the compressive strength. TGA Test presented the thermal stability of EAF slag replaced concrete for up to approximately 660°C before degradation starts. Overall, the results shows that a 90% replacement of fine aggregate with EAF slag using the R1 particle size range (0.8–2.36 mm) achieved the highest compressive strength of 54.75 MPa. Supported by favorable elemental (Ca and Si) and compound-level (Ca(OH)2 and SiO2) microstructural characteristics, this mix was identified as the optimal replacement ratio in this study. These findings could provide
insights for the potential of EAF slag as a sustainable and performing alternative to natural fine aggregates. This also alignes with environmental and structural demands in modern construction practices.
Keywords: Electric Arc Furnace (EAF) Slag, Concrete, Fine Aggregate Replacement, Compressive Strength, Microstructure
Subject Area: TH1000-1725 Systems of building construction Including fireproof construction, concrete constructio
Taskbooster: web-based productivity and collaboration task management system
Get PDFThis project is regarding the development of a web-based task management system that incorporates productivity and collaboration features. In the age of modernization, the demand for task management system has become increasingly essential typically after the widespread COVID-19 pandemic. Many individuals struggle to coordinate tasks effectively. The advance of technology also results in distractions which often disrupt the attention of users and lead users to become inefficient and reduce productivity. This shows the need for a system that helps users to maintain their focus and boost their productivity. This project presents the development of a web-based system of task management with productivity and collaborative features called TaskBooster. This web-based system is designed to address common inefficiencies in task organization and team collaboration by integrating real-time collaborative tools that streamline work arrangements. In addition, TaskBooster implements personalized productivity features to track and enhance productivity over time. Besides the mentioned above, this proposed system also focuses on the ease of use for its simplified user interface to ensure that new users can navigate the platform and understand its basic functions within the first fifteen minutes of use. The objective of the combination of intuitive design with robust functionality of TaskBooster is to provide an efficient and user-friendly solution for both individual and team task management to enhance the overall productivity as well as foster effective collaboration in a digital environment. The target users for this system are managers and employees. The key features of this platform include login module, a collaborative feature, to-do list, a communication feature, a Pomodoro clock, analysis charts and a calendar feature. This project is expected to use Agile methodology and tools such as hardware and software to develop this web-based task management system
Kindergarten management system
Get PDFThis project proposes the development of a comprehensive Kindergarten Management System to streamline administrative operations, enhance communication between teachers and parents, and improve lesson planning for educators. The system aims to address inefficiencies in current manual processes by offering an intuitive and user-friendly web-based solution. Key features include attendance tracking, billing management, lesson planning tools, a shared school calendar, and a communication platform for parents and teachers. The project leverages modern technologies such as PHP, HTML5, CSS, JavaScript, and MySQL to create a robust, scalable, and accessible system. By adopting principles from Extreme Programming (XP), the development process ensures flexibility, high code quality, and alignment with user needs. The proposed system will significantly reduce administrative workload, foster better collaboration between teachers and parents, and empower teachers with tools to create and manage lesson plans effectively. This project aims to deliver a reliable, efficient, and comprehensive solution tailored to the unique needs of kindergartens
Construction of nptII–mtsfGFP fusion gene construct by overlap extension PCR
Get PDFIn plant transformation, the Agrobacterium-mediated system (AMT) is widely used due to deliver transgenes into multi-layered plant cells without causing damage. Previously, the GatewayTM-compatible binary vectors, pG103 and pG104 were built to enable convenient transgene insertion. For the selection of transformed cells, plasmid vectors pG103 and pG104 harbor the selectable markers neomycin phosphotransferase II (NptII) and mitochondrial recoded neomycin phosphotransferase II (mtNptII) genes, respectively, which confer resistance to aminoglycoside antibiotics for nuclear and mitochondrial transformation. To facilitate visualization of the protein expression of the gene of interest (GOI), a reporter gene is often translationally fused it. The green fluorescent protein (GFP) gene is widely used as a reporter gene. This project used mitochondrial recoded superfolder GFP (mtsfGFP) gene, which encode the same superfolder GFP protein, is designed for expression in either the host’s nucleus and mitochondria. This project aimed to fuse the NptII and mtNptII with mtsfGFP using overlap extension PCR (OE-PCR). A 3-step OE-PCR approach using megaprimers was employed. However, due to the formation of secondary structures of the megaprimer during the PCR reaction, non-specific amplicons were generated. To eliminate these non-specific amplicons and obtain the desired amplicons, parameters such as primer and template DNA concentrations, number of thermal cycles, and annealing temperature, were performed for each step of the OE-PCR. Consequently, amplicons carrying the NptII- mtsfGFP and mtNptII- mtsfGFP fusion genes were successfully generated. In the future, these amplicons will be cloned into the Agrobacterium binary vectors for host transformation. They will facilitate qualitative and quantitative analysis of transgenes in the host’s nucleus and mitochondria
Car pooling application for UTAR Kampar student
Get PDFThis project lies within the field of web-based application development, specifically targeting intelligent carpooling systems for university communities. It focuses on the design and implementation of a carpooling platform tailored for UTAR Kampar students, addressing the lack of a centralized, reliable, and affordable car-sharing solution. The primary objective is to provide a cost-effective alternative to commercial ride-hailing services like Grab by facilitating a student-exclusive platform to offer and request rides based on real-time and recurring schedules. Key features include user registration, ride listings, bookings, and ride management, with Google Maps API integration for geolocation and route assistance. Dialogflow is employed to deliver an AI-powered chatbot that helps users search for available rides through natural language interaction. A key novelty introduced in the second phase is timetable-based ride creation and search, which allows students to auto-generate recurring ride offers based on their weekly class schedules. This feature significantly reduces manual input, increases consistency in ride availability, and streamlines the carpooling experience by aligning with students' academic timetables. The project followed the Agile methodology throughout the Software Development Life Cycle (SDLC), incorporating iterative development, continuous feedback, and incremental improvements. The implemented prototype has been tested to enable smooth interaction between drivers and passengers, improve time efficiency in finding suitable rides, and foster a stronger community-based transportation culture. Conclusively, this system has shown promising results in reducing transportation friction among students and introduces a novel approach by integrating academic timetables with carpool scheduling—a unique feature not commonly found in existing ride-sharing platforms