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All Journal Journal of Noesantara Islamic Studies Journal of Moeslim Research Technik Journal of Selvicoltura Asean Research Psychologie, Orientation et Conseil Journal of Tecnologia Quantica Journal of Loomingulisus ja Innovatsioon Research of Scientia Naturalis Journal of Biomedical and Techno Nanomaterials Journal of Social Entrepreneurship and Creative Technology Journal of Humanities Research Sustainability Journal of Multidisciplinary Sustainability Asean Islamic Studies in the World Journal Markcount Finance Sharia Oikonomia Law Journal Journal Neosantara Hybrid Learning Journal of World Future Medicine, Health and Nursing Pengabdian: Jurnal Abdimas Journal Emerging Technologies in Education Rechtsnormen: Journal of Law
Nurul Huda
Universiti Utara
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Physics Other

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Artificial Intelligence in Precision Medicine: Transforming Genetic-Based Diagnostics and Patient Care Fitriah Handayani; Nurul Huda; Benny Novico Zani; Muntasir Muntasir
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i4.2520

Abstract

Precision medicine aims to tailor healthcare strategies to individual genetic, environmental, and lifestyle factors, enhancing diagnostic accuracy and treatment efficacy. Traditional approaches to genetic-based diagnostics often face challenges such as high complexity, large-scale data interpretation, and time-intensive analyses. Artificial intelligence (AI) offers transformative potential by enabling rapid, data-driven analysis of genomic information, supporting personalized patient care, and improving clinical decision-making. This study investigates the role of AI in enhancing genetic-based diagnostics and patient care within precision medicine. A systematic review and critical analysis were conducted, integrating findings from peer-reviewed research, clinical reports, and AI-based diagnostic applications. The methodology focused on evaluating AI algorithms for genetic variant detection, risk prediction, and therapeutic recommendations, as well as assessing their clinical integration and outcomes. Results indicate that AI significantly improves the speed, accuracy, and interpretability of genomic analyses, facilitating early disease detection, individualized treatment planning, and predictive risk assessment. Challenges include data privacy, algorithmic transparency, and the need for robust validation in diverse populations. The study concludes that AI integration in precision medicine represents a pivotal advancement in genetic diagnostics and patient-centered care, offering scalable solutions for complex healthcare challenges. Ethical, regulatory, and technical considerations are essential to ensure safe, equitable, and effective implementation in clinical practice.
PUBLIC POLICY ANALYSIS OF DECENTRALIZED NATIONAL ELECTRONIC HEALTH RECORDS USING BLOCKCHAIN TECHNOLOGY Mulyaningsih Mulyaningsih; Nurul Huda; Nina Anis
Journal of World Future Medicine, Health and Nursing Vol. 4 No. 4 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v4i4.4068

Abstract

National electronic health record (EHR) systems face persistent challenges related to interoperability, data security, and fragmented governance structures, particularly within centralized architectures that limit real-time data exchange across healthcare institutions. This study aims to analyze public policy implications of implementing decentralized national EHR systems using blockchain technology, with emphasis on governance transformation, regulatory alignment, and system performance. A qualitative-dominant mixed-methods approach is employed through comparative policy analysis, secondary data evaluation, and stakeholder interpretation. Results indicate that blockchain-based EHR systems significantly improve interoperability (88% vs 62%), reduce data breach incidence (3 vs 18 cases per million records), and enhance patient data accessibility (score 91 vs 65). Inferential findings confirm statistically significant improvements in system efficiency and governance performance. The study concludes that decentralized blockchain-enabled EHR systems offer substantial advantages over centralized models, not only in technical performance but also in reinforcing transparency, trust, and data sovereignty within national health governance frameworks, while requiring adaptive regulatory reforms for sustainable implementation.
Optimizing the Role of Husbands in Childbirth Assistance through Education and Simulation of Nonpharmacological Techniques in Balikpapan Nila Trisna Yulianti; Nurul Huda
Pengabdian: Jurnal Abdimas Vol. 4 No. 2 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/abdimas.v4i2.3747

Abstract

Background. Childbirth is a challenging experience, and the involvement of the husband in providing emotional and physical support can significantly impact maternal outcomes. However, paternal involvement in non-pharmacological labor support remains underexplored, particularly in Balikpapan. Purpose. This study aimed to optimize the role of husbands in supporting their wives during labor through education and simulation of non-pharmacological techniques. Method. The research employed a quasi-experimental design with a pre-test and post-test approach, involving 50 couples from Balikpapan. Participants attended educational sessions on non-pharmacological pain relief techniques, followed by simulation exercises where husbands practiced these methods. Results. The results showed a significant increase in husbands’ knowledge, with the mean post-test score rising from 35% to 78%. Moreover, husbands demonstrated a 60% improvement in applying non-pharmacological techniques during simulated labor scenarios. Conclusion. The findings suggest that targeted education and simulation effectively enhance husbands’ preparedness to provide essential support during labor, contributing to improved maternal comfort and reduced anxiety. This study highlights the importance of including paternal education in prenatal care programs, advocating for a more family-centered approach to childbirth. Future research should explore the long-term effects of such interventions and their applicability across diverse cultural contexts.
Social Media as an Informal Learning Environment: Opportunities and Risks for Student Development Maryanti Sawitry; Irene Rosalina; Vita Pujawanti Dhana; Harlina Harja; Nurul Huda
Journal Emerging Technologies in Education Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jete.v3i4.2509

Abstract

Background. Social media platforms have increasingly become informal learning environments where students engage in knowledge sharing, collaboration, and skill development outside formal educational settings. Purpose. This study aims to explore the opportunities and risks associated with social media as an informal learning environment, focusing on its influence on cognitive, social, and emotional development. Method. A mixed-methods research design was employed, combining surveys of 250 students with semi-structured interviews to capture qualitative insights into learning behaviors, engagement patterns, and perceived benefits and drawbacks of social media usage. Results. Findings indicate that students leverage social media for collaborative learning, problem-solving, and information seeking, enhancing critical thinking and communication skills. However, exposure to inaccurate content, online distractions, and social comparison negatively impacted focus, motivation, and emotional well-being.   Conclusion. The study concludes that while social media can serve as a valuable informal learning environment, structured guidance, digital literacy education, and awareness of potential risks are essential for maximizing benefits and mitigating harms.
The Legal Implications of Artificial Intelligence in Criminal Justice: From Surveillance to Sentencing Md Shodiq; Rina Farah; Nurul Huda
Rechtsnormen: Journal of Law Vol. 4 No. 3 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/rjl.v4i3.3832

Abstract

Background. The increasing integration of Artificial Intelligence (AI) in criminal justice systems has raised significant concerns regarding its legal implications, particularly in surveillance and sentencing practices. As AI technologies become more embedded in law enforcement and judicial decision-making, questions surrounding privacy, accountability, and fairness have become central to discussions of legal reform. Purpose. The study aims to evaluate the extent to which current legal frameworks can address these challenges and propose reforms to ensure ethical use of AI in criminal justice systems. Method. A qualitative methodology is employed, using semi-structured interviews with legal experts, policymakers, and AI practitioners, alongside secondary data from case studies and policy documents. Results. The findings indicate that while AI has the potential to enhance efficiency, it often perpetuates existing biases and lacks sufficient oversight, leading to unjust outcomes. Conclusion. The study concludes that robust legal frameworks are essential to prevent the misuse of AI in criminal justice and to protect fundamental rights. This research contributes to the growing body of literature on AI's intersection with law and offers practical recommendations for legal reforms.
Co-Authors Amin Zaki Ardi Azhar Nampira Benny Novico Zani Busnawir Busnawir Dyah Retno Wulan ernikawati ernikawati Faisal Razak Fitriah Handayani Handoko, Yudo Harlina Harja Haziq Idris Ira Wulan Sari Irene Rosalina John Smith M Faisal Makhrus Ali Martinis Yamin Maryanti Sawitry Md. Shodiq Miksusanti Miksusanti Ming Pong Minnah El Widdah Misbahul Khairani Mujiburrohman Mulyaningsih Muntasir, Muntasir Nila Trisna Yulianti Nina Anis Ninik Sri Rahayu Wilujeng Nong Chai Pedro Silva Puspaningrum, Dian Rahmadani Rahmadani Rimba Krisnha Sukma Rina Farah Rinah Farah Romiyilhas Romiyilhas Rusydi Rusydi Siti Hasanah Siti Shofiah Syafiq Amir Vita Pujawanti Dhana Yoosita Aulia Zain Nizam