UTAR Institutional Repository (Universiti Tunku Abdul Rahman)
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A dashboard system for a student's academic performance management.
Get PDFThis project is a dashboard system for a student’s academic performance management. This is a development-based project, and the area of study is the Information System domain. This project is a platform for students’ academic performance management to manage key performance indicators, including grades, attendance, goal reflection and assignment progress. Besides that, this project also allows students and teachers to access real-time updates on performance trends. This is because the application has the feature of interactive data visualization and report generation. On the other hand, the system enables teachers to input and update academic records seamlessly. Besides, the system will extract important information from the data uploaded by teachers, such as spreadsheets or integrated databases. Therefore, the application also provides analysis and personalized feedback for students based on their academic progress. The system will automatically identify students who are at risk and generate alerts for intervention. After the system has done the analysis, it will allow users to generate comprehensive reports in a format. When the dashboard is accessed, it provides users with a clear and concise view of academic performance metrics. On the other hand, the system also supports accessibility across devices, ensuring that both students and teachers can access it from anywhere. Admin is empowered to manage users, assign courses, manage course data, and monitor system usage through the Admin Dashboard
Financial advisory and management system
Get PDFThe Financial Advisory and Management System project addresses the growing need for accessible, user-centric financial tools tailored for Malaysian users, focusing on empowering individuals to manage their finances effectively through advanced technology. This study develops an Android application using Kotlin and Firebase (Firestore) to enhance expense categorization, financial literacy, and goal tracking. The system enables users to create customizable expense categories, track spending with real-time data synchronization, and visualize financial trends through line and pie charts on the Transaction and Expenses Details Pages, ensuring accurate and flexible expense management. This financial education hub empowers users with personalized insights derived from their unique spending patterns and a community comparison feature that leverages real, anonymized data from other users. With the support of an AI assistant built on the Google Gemini API, the platform provides tailored, contextual advice to help users better manage their finances. Basic goal tracking functionality is implemented on the Goal Page, with plans to integrate the Days Needed Calculation Algorithm for real-time progress tracking in future iterations. The project employs a secure framework with Firebase Authentication, ensuring general data protection regulation (GDPR) compliance, and lays the foundation for future enhancements, including Google's ML Kit Text Recognition API integration for automated receipt scanning and Google's Speech Recognition API for using voice command to input the transaction. This research contributes to the field of personal finance technology by addressing limitations in existing systems, such as manual data entry and lack of financial education, through a free, culturally relevant solution designed for long-term financial stability
Indoor navigation for visually impaired
Get PDFThe increasing prevalence of visual impairments globally has highlighted the importance of effective assistive technologies to enable independent navigation for the visually impaired in indoor environments. Traditional indoor navigation systems often suffer from high costs, signal interference, and reliance on pre-installed infrastructure, making them inaccessible to many. This project proposes a cost-effective and infrastructure-free indoor navigation system that leverages a smartphone's camera and advanced computer vision. The system's core is a novel localization approach that uses a DINOv2 vision transformer to generate robust semantic embeddings from real-time images. For superior accuracy, initial embedding comparisons are verified by a Vision-Language Model (VLM), which provides contextual understanding of the scene. To handle dynamic environments, the system integrates YOLOv8-seg and Stable Diffusion 2.0 to detect and remove people from the camera feed, ensuring reliable performance. Implemented as a Flutter mobile application with a high-performance FastAPI and Supabase backend, the system provides users with step-by-step guidance along pre-recorded visual routes, delivering clear instructions via audio feedback and a hands-free voice assistant. By integrating state-of-the-art deep learning models into an accessible platform, this project addresses the limitations of existing solutions and contributes meaningfully to advancing assistive technology for the visually impaired community
Musical signature identification and plagiarism detection through feature extraction and analysis
Get PDFMusic information retrival (MIR) systems are introduced to counter musical borrowing and unintentional plagiarism in the present music industry. Music plagiarism detection is a complex task, as similarity may arise not only from melodic lines but also from rhythm, harmony, and timbre. This system introduces an approach that integrates multi-dimensional audio features with segment-based analysis to improve detection accuracy and interpretability. Extracted features include harmonic descriptors (CENS, CQT, tonnetz, harmonic n-grams), rhythmic descriptors (tempogram, onset autocorrelation), timbral descriptors (MFCC), and spectral texture measures (spectral contrast, centroid, rolloff, bandwidth, flatness). Database songs are segmented into overlapping windows of varying lengths, while query tracks are segmented consistently, allowing robust local-to-local comparisons. A weighted similarity model balances contributions from all features and normalizes results even when certain descriptors are unavailable. Potential plagiarism is flagged when segment similarities exceed adaptive thresholds, and is presented in a ranked list. To support expert evaluation, the system employs large language models (LLMs) to generate textual analyses of the top matches, highlighting how melodic, rhythmic, harmonic, and timbral evidence supports or weakens plagiarism claims. The aim is to provide music experts with clear, evidence-driven insights, enabling more efficient and transparent decision-making
Investigating the drivers and barriers of construction innovation in Malaysia
Get PDFThe construction industry is a cornerstone of economic development, yet it remains comparatively slow in adopting innovation relative to other sectors like manufacturing and information technology, especially in Malaysia. This
study investigates the drivers, barriers, and underlying factors influencing construction innovation in the Malaysian construction industry. Motivated by the growing importance of innovation for competitiveness and sustainability, the research combines an extensive literature review with a structured questionnaire survey of 150 practitioners, including developers, consultants, and contractors in the Klang Valley region. Rigorous statistical analyses were
applied to ensure the robustness of findings, including reliability testing, normality assessment, and factor analysis. The results identified technology push, environment and sustainability, technological capability, strategic
alliances, and subsidies as the most critical drivers, reflecting both global trends and local industry needs. Conversely, lack of financial resources, operational resource gap, lack of technical capabilities, lack of incentives, and
inappropriate legislation emerged as the most significant barriers. The factor analysis further revealed six latent drivers and five latent barriers, illustrating that innovation is influenced by institutional, organisational, market, and behavioural dynamics. Respondents also expressed cautious optimism about the future, acknowledging the importance of innovation for competitiveness while noting persistent concerns over preparedness and resource allocation. The study provides important implications for practice, policy, and academia in Malaysia, as well as for other developing countries facing similar challenges
or seeking to develop a more future-ready construction industry. Overall, the findings underscore the need for coordinated strategies to overcome barriers and transform innovation awareness into sustained industry advancement.
Keywords: construction industry; construction innovation; drivers; barriers; Malaysia
Subject Area: HD9715-9717.5 Construction industr
Smart sustainable city readiness in Malaysia
Get PDFUrbanisation is accelerating in developing countries, leading to increased resource consumption, environmental degradation, and challenges in sustainable urban planning. Smart sustainable cities have emerged as integrated solutions that leverage technology and efficient resource management to
support environmentally responsible and livable urban development. While most studies focus on defining smart sustainable cities and their technological components, limited research evaluates the readiness of cities, especially in Malaysia, for such a transformation. Evaluating city readiness and prioritising quality of life are key to a successful, inclusive shift to sustainability. Thus, this
study aims to evaluate the readiness level of Malaysian cities towards a smart sustainable city. Four main criteria for assessing the readiness level of cities for becoming smart sustainable cities were identified through literature review, namely Human Aspects, Technology Aspects, Economic Aspects, and Governance Aspects. Eight strategies to improve the readiness level were then discovered such as Educational and Awareness Campaigns, Financial Incentives and Subsidies, Infrastructure Development, Policy and Regulatory
Frameworks, Comprehensive Data Strategy, Pilot and Scale Smart Solutions, Planning for Long-Term Sustainability, and Secure Funding and Resources. Questionnaires were distributed to residents in Putrajaya, Cyberjaya, Kuala Lumpur, and Shah Alam, with 100 valid responses collected. Data analysis
results indicated that Technology Aspects ranked highest among smart sustainable cities, while Human Aspects led among non-smart sustainable cities. Infrastructure development was found to be the most effective improvement strategy. The result of Spearman’s Correlation Test showed that citizens’
readiness to use IT-based services and technologies is the most significant criteria and the organisation of campaigns to increase public awareness is a noteworthy strategy. Besides, significant differences in smart sustainable city
readiness were observed across age, education level, income level, ethnicity, gender, marital status, residential state, and income type. This study supports Malaysia’s smart sustainable cities transition by assessing cities' readiness and offering practical strategies to guide agencies like Jabatan Kerja Raya and Construction Industry Development Board in aligning infrastructure and construction with smart sustainable goals.
Keywords: smart sustainable city, sustainability, city readiness, strategies, urbanisation
Subject Area: HT165.5-169.9 City plannin
Addressing challenges and solutions in teaching speaking skills to non-English course students at UTAR
Get PDFThis study investigates the challenges and solutions in teaching speaking skills to non-English course students at Universiti Tunku Abdul Rahman (UTAR). Using a mixed-method approach, data were collected from 36 lecturers from the Faculty of Arts and Social Science (FAS) and the Centre for Extension Education (CEE) in Kampar campus. The research aimed to address two key questions which are the difficulties lecturers face in teaching speaking skills and the strategies they propose to improve students’ oral proficiency. Findings revealed that psychological barriers such as anxiety, low confidence, and fear of making mistakes, as well as linguistic difficulties such as limited vocabulary, weak sentence structure, pronunciation issues, and dependent on mother tongue usage were a major challenge to students’ speaking development. These results align with the existing literature and highlight the impact of both affective and linguistic factors on oral performance. The study also identified several effective strategies, such as role plays, language games, trial-and-error approaches, reading aloud, and the integration of technology were widely endorsed by lecturers. Additionally, creating a safe and supportive classroom environment and tailoring speaking tasks to students’ academic backgrounds were emphasized as crucial for enhancing participation and confidence. The implications of these findings highlights the importance of adopting interactive, learner-centered teaching methods and providing institutional support for language lecturers. While the study contributes valuable insights, its scope is limited by the sample size, location, and cross-sectional design. Recommendations for future research include expanding the sample across faculties and institutions, conducting longitudinal studies, and incorporating student perspectives to complement lecturers’ views. In conclusion, this study highlights the importance of psychological and linguistic difficulties in shaping speaking performance among non-English course students and provides practical strategies to address these challenges. The results contribute to a better understanding of how empathetic, adaptive, and technology-enhanced teaching approaches can foster more effective and engaging speaking lessons in ESL contexts
Exploring cultural and gender-based variations in emoji interpretation among Malaysian youth
Get PDFThe study investigates how culture and gender shape the interpretation and usage of emojis among Malaysian youth. Data was collected through a pre-survey to identify frequently used and ambiguous emojis, along with in-depth interviews with eight participants representing different ethnic and gender groups. The analysis employed Social Semiotics to interpret emojis as semiotic resources situated in cultural and digital practices, alongside Systemic Functional Linguistics (SFL) to examine their ideational, interpersonal, or textual meta-functions. Findings reveal that while certain emojis retain culturally embedded meanings, online culture and digital trends exert a stronger influence on interpretation and usage. Emojis are frequently employed as substitutes for sensitive or taboo topics, with interpretations shaped by global trends, peer influence, and shared social contexts. Gender differences also emerged, with female participants displaying greater caution and sensitivity in emoji use by employing them as politeness markers and face-saving devices more often than their counterparts. This study extends prior research by showing how localized cultural practices persist but increasingly blend with inline subcultural norms. These findings contribute to the understanding of emojis as dynamic meaning-making resources in multicultural digital communication
A quantitative study on the performance of construction industry in IR 5.0 evolution: using conceptual model approach
No full textThe construction industry currently faces limitations in knowledge and understanding of Industrial Revolution 5.0 (IR 5.0), which poses challenges to its adoption. This research project aims to investigate the performance of the construction industry in the context of IR 5.0 evolution. The objectives are: (i) to identify the variables that affect performance, (ii) to examine the relationship between readiness and intention toward performance, and (iii) to explore the impact of readiness and intention on performance. The study adopts a conceptual framework based on the Theory of Reasoned Action (TRA), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Theory of Organisational Readiness for Change (TORC). A quantitative approach was employed, where descriptive analysis was conducted using IBM SPSS, and Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied through SmartPLS to assess both the measurement and structural models. The findings indicate that readiness does not significantly influence the performance of the construction industry in IR 5.0, whereas intention demonstrates a significant relationship and positive impact on performance. In conclusion, the study emphasizes that intention plays a more critical role than readiness in enhancing construction industry performance in IR 5.0. These results contribute to theoretical understanding and provide practical insights for policymakers and construction players in fostering successful IR 5.0 adoption.
Keywords: Quantitative analysis, IR 5.0 Revolution, Performance, Construction Industry, Readiness and Intention
Subject Area: HA29-32 Theory and method of social science statistic
Investigating the relationship between the urban heat island effect and short-duration extreme rainfall in Kuala Lumpur
No full textUrbanisation significantly alters land surface characteristics, leading to the intensification of the urban heat island (UHI) effect, which may influence the short-duration extreme rainfall. This study investigates the relationship between UHI intensity and short-duration extreme rainfall in Kuala Lumpur through an integrated remote sensing, machine learning and statistical approach. Landsat imagery from 2007, 2015 and 2023 was used to analyse spatiotemporal changes in land use and land cover (LULC) and to estimate land surface temperature (LST). LULC classification was performed using Support Vector Machine (SVM) and Random Forest (RF) algorithms, while LST was estimated using the Single Channel (SC) algorithm and surface urban heat island intensity (SUHII) was subsequently derived from the LST data. Hourly rainfall data exceeding the 99th percentile from 2007 to 2023 were used to assess spatiotemporal variation, diurnal distribution and trends. Statistical relationships between SUHII and hourly extreme rainfall were examined using the coefficient of determination (R²) and Kendall’s Tau (τ). Results show that SVM consistently outperformed RF in terms of overall accuracy and kappa coefficient across all study years. Built-up areas and SUHII both exhibited a net increase, particularly in northern Kuala Lumpur, likely due to intense urbanisation and industrial activities. The number of hourly extreme rainfall events also increased, especially during late afternoon and evening hours. However, the mean intensity of extreme rainfall events remained relatively stable. Correlation analysis identified moderate, statistically significant relationships between the annual SUHII and the annual total number of hourly extreme rainfall events at four of nine stations (R² = 0.2530 - 0.3088; τ = 0.3616 - 0.4593; p < 0.05). These findings suggest that urban-induced heating may contribute to enhanced localised convective rainfall. It is recommended that UHI mitigation measures, such as green infrastructure and climate-sensitive urban planning, be prioritised to manage future rainfall-related flood risks in urban environments.
Keywords: Urban Heat Island; Land Surface Temperature; Land Use and Land Cover; Remote Sensing; Machine Learning; Short-Duration Extreme Rainfall; Rainfall Analysis; Relationship
Subject Area: TA170-171 Environmental Engineerin