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All Journal International Journal of Evaluation and Research in Education (IJERE) Sinergi International Journal of Education Toplama
Mansor, Nur Suhaili
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Humanities Education Environmental Science Languange, Linguistic, Communication & Media Social Sciences

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Prototyping a Web-Based Application for Remedial Education Data Management Haruna, Isyaku Uba; Awang, Hapini; Mansor, Nur Suhaili; Ibrahim, Huda Hj; Azni, Syafiqah; Khamis, Shakiroh
Sinergi International Journal of Education Vol. 2 No. 2 (2024): May 2024
Publisher : Yayasan Sinergi Kawula Muda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61194/education.v2i2.256

Abstract

The Sistem Pengurusan Data Program Pemulihan Khas (SPD) is a web-based application that focuses on managing data for a remedial education program in 28 primary schools across Cameron Highlands, Pahang. It is a computerized system designed to replace the manual system that currently uses Microsoft Excel forms to manage pupils' information. The system's features enable tracking of the pupils' academic progress and providing data for upper management decision-making. This system is intended for use by remedial teachers to manage pupils' information, school authorities to monitor the program, and education officers at the district level. In developing the system, a system prototyping development methodology was adopted. Functional requirements were gathered through meetings with clients and a prototype called "SPD" was created based on these requirements. A field study was conducted to assess the prototype's usability, and the results indicated that SPD is straightforward and easy to use. The study contributes to understanding the system requirements and user interface of the web-based application for managing information and data related to remedial education.
Modeling blockchain technology in assessment management: the initial readiness investigation Shuhaimi, Joharri; Awang, Hapini; Al-Mashhadani, Abdulrazak F. Shahatha; Jafar, Mohd Fairuz; Mansor, Nur Suhaili
International Journal of Evaluation and Research in Education (IJERE) Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v14i1.28416

Abstract

The implementation of the school-based assessment (SBA) came with a system as part of the effort to reduce the workload of teachers in managing the SBA. However, a traditional system is costly and heavily centralized, frequently leading to impediments, delays, irregularities and may even create opportunities for dishonest activities. To enhance the existing traditional system, integrating emerging blockchain technology (BC) is proposed. Given the challenges, complaints, and rejection faced by traditional assessment management systems, this paper presents a conceptual framework based on the technology acceptance model (TAM) and diffusion of innovation (DOI) to examine pre-university teachers’ perception of implementation and readiness to adopt BC-based project paper management (BPPM) which is subsequently verified through a qualitative study. This study employs a process that consists of three main steps: a thorough review of existing literature, thematic analysis, and the process of gathering and determining readiness factors. Teachers’ perspectives were successfully gathered from 59 pre-university teachers by posting semi-structured questions in a Telegram group of Malaysian pre-university teachers. The study found that most pre-university teachers support the BPPM implementation with the condition that the system can address two primary concerns: server scalability and confidentiality issues. The effectiveness of BPPM implementation depends on its capacity to meet user needs and expectations while delivering clear benefits, along with superiority compared with existing systems.
A CONCEPTUAL FRAMEWORK FOR AI SELF-HEALING FOR BIAS MITIGATION: A PROACTIVE ARCHITECTURAL PROPOSAL Harianja, Harianja; Syam, Elgamar; Wahab, Alawiyah Abd; Ibrahim, Huda; Awang, Hapini; Mansor, Nur Suhaili; Sidik, Adi Permana
TOPLAMA Vol. 3 No. 2 (2026): TOPLAMA
Publisher : PT Altin Riset Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61397/tla.v3i2.509

Abstract

As the adoption of Artificial Intelligence (AI) continues to expand across various sectors, the issue of bias in training data has emerged as a significant ethical and technical challenge. AI systems are commonly trained using large-scale datasets collected from digital environments such as the internet, social media, and public databases. These datasets often contain historical inequalities, stereotypes, and unbalanced representations of certain demographic groups. Consequently, AI models may unintentionally replicate and amplify these biases in their predictions or decisions. This situation becomes particularly concerning when AI is used in high-stakes domains such as recruitment, healthcare, financial services, and public policy. Most existing bias mitigation strategies rely on reactive approaches, such as adjusting model outputs or modifying datasets after bias has already been identified. While these methods can reduce certain forms of discrimination, they often require significant manual intervention and may not effectively address bias in dynamic data environments. This research proposes a conceptual framework for an AI self-healing system designed to autonomously detect and correct bias in training data before it influences model outcomes. The proposed framework integrates four key modules: Data Monitoring, Bias Analysis, Automated Bias Correction, and a Feedback Loop and Validation mechanism. Together, these components create a continuous workflow that allows the system to identify bias patterns, apply corrective strategies, and verify fairness before data is used for model training. This framework offers a proactive and sustainable approach to bias mitigation while supporting the development of more ethical, robust, and accountable AI systems.
MOBILE SECURITY PRACTICES AMONG MALAYSIAN CITIZENS: A SURVEY OF RISK AWARENESS AND PROTECTIVE BEHAVIORS QIN, QIN; Mansor, Nur Suhaili; Awang, Hapini; Ibrahim, Huda; Sidik, Adi Permana
TOPLAMA Vol. 3 No. 2 (2026): TOPLAMA
Publisher : PT Altin Riset Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61397/tla.v3i2.512

Abstract

Mobile phones have become an important part of Malaysian youth's daily lives, and as easy as it is to get our hands on a mobile, the growing issues that follow raise alarms for cybersecurity. WordPress site. Although there has been a recent influx of online scam and privacy breach reports, little still exists on how ordinary users perceive mobile security, or if their behaviors are consistent with good risk mitigation practices. This study aims to examine the relationships that exist among mobile security confidence, user practices, and incident experiences with the gender of Malaysian youth. Using an eight-sectioned structured survey as an evaluation instrument, key findings are mainly gleaned from users who report medium levels of confidence in their mobile malware knowledge and overall adoption of protective behaviors such as keeping software updated, only using trusted sources to download apps, and using biometrics. A total of 38.1% of respondents, meanwhile, admitted to previous security incidents largely borne out of the presence of outdated systems and a lack of oversight elements in place for vetting third-party applications. in a rapidly digitizing society. Yet without habitual practice and supportive system design, awareness alone may not be enough.
Co-Authors Al-Mashhadani, Abdulrazak F. Shahatha Awang, Hapini Azni, Syafiqah Elgamar Syam Harianja, Harianja Haruna, Isyaku Uba Ibrahim, Huda Ibrahim, Huda Hj Jafar, Mohd Fairuz Khamis, Shakiroh QIN, QIN Shuhaimi, Joharri Sidik, Adi Permana Wahab, Alawiyah Abd