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All Journal i-Latinnotary Journal: Internasional Journal of Latin Notary Toplama
Huda Ibrahim
Universiti Utara Malaysia
Humanities Astronomy Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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VIRTUAL HUB FOR SMALL MEDIUM ENTERPRISES (SMES) IN INDONESIA AND MALAYSIA (POSH COSH AND HERBAL PRODUCT CASES) Huda Ibrahim; Suwannit Chareen Chit; Irma Rachmawati
International Journal of Latin Notary Vol 1 No 2 (2021): Internasional Journal of Latin Notary, Vol. 1, No. 2, March 2021
Publisher : Magister Kenotariatan Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (241.139 KB) | DOI: 10.55904/journal.v1i2.11

Abstract

ASEAN countries are a melting pot of 617 million people with rich culture and unique skills and can only be found in this part of the world. Over the decades, this region had seen immense transformation due to the economic boom but still retained its historical identity. It is no wonder that one can see a blend of modern sophistication and traditional lifestyle existing side-by-side in ASEAN Countries today. Small Medium Enterprises (SMEs) are integral to the ASEAN Member States' economic development and growth. They vastly outnumber larger enterprises in both the number of establishments and share of the labor force they employ. The result of this hub requires active participation by multiple stakeholders, particularly the entrepreneurs. Therefore, their views are valuable to us and will be taken into consideration. It is hoped that the principles of openness, user-centricity, and stakeholder participation are upheld.
HOT TOPICS AND RESEARCH TRENDS IN THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN SMART MANUFACTURING Liu Yonggang; Hapini Awang; Nur Suhaili Mansor; Huda Ibrahim
TOPLAMA Vol. 3 No. 3 (2026): TOPLAMA
Publisher : PT Altin Riset Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61397/tla.v3i3.538

Abstract

With the advancement of Industry 4.0, artificial intelligence that integrates Internet of Things (IoT), big data (BD), edge computing (EC), digital twins, haptic feedback, and other technologies is penetrating various aspects of smart manufacturing, such as predictive maintenance, material design, automatic fault detection, and so on. Based on sampling data extracted from Scopus database between 1986 and 2025, this study employs a bibliometric analysis method to systematically analyse research trends, knowledge structures, and future directions in the field of artificial intelligence and smart manufacturing. The results show that this cross-disciplinary research between artificial intelligence and smart manufacturing has witnessed significant upward growth in recent years, especially since 2017. The top 10 most cited documents, most related documents, some productive authors, and high-frequency keywords have been identified. This study not only helps researchers comprehensively grasp the development trajectory but also provides directional guidance and knowledge map support for subsequent research.
A CONCEPTUAL FRAMEWORK FOR AI SELF-HEALING FOR BIAS MITIGATION: A PROACTIVE ARCHITECTURAL PROPOSAL Harianja Harianja; Elgamar Syam; Alawiyah Abd Wahab; Huda Ibrahim; Hapini Awang; Nur Suhaili Mansor; Adi Permana Sidik
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; Nur Suhaili Mansor; Hapini Awang; Huda Ibrahim; Adi Permana Sidik
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 Adi Permana Sidik Alawiyah Abd Wahab Elgamar Syam Hapini Awang Harianja Harianja Liu Yonggang Nur Suhaili Mansor QIN QIN R. Irma Rachmawati, R. Irma Suwannit Chareen Chit