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All Journal JOIV : International Journal on Informatics Visualization JURNAL DINAMIKA VOKASIONAL TEKNIK MESIN SYAMIL: Jurnal Pendidikan Agama Islam (Journal of Islamic Education) Data Science: Journal of Computing and Applied Informatics JISIP: Jurnal Ilmu Sosial dan Pendidikan JUPE : Jurnal Pendidikan Mandala Journal of Computer Networks, Architecture and High Performance Computing Jounal of Education and Teaching (JET) Jurnal Ilmiah Teknik (JUIT) SYAMIL: JURNAL PENDIDIKAN AGAMA ISLAM (JOURNAL OF ISLAMIC EDUCATION) Jurnal Pengabdian Masyarakat Bangsa Journal Of Engineering Sciences (Improsci)
Fahmy Ferdian Dalimarta
Universitas Muhammadiyah Tegal, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Transforming Islamic and Moral Education with Generative AI: A Statistical Systematic Review Budiyanto, Budiyanto; Al Matari, Ali Said; Adiyono, Adiyono; Dalimarta, Fahmy Ferdian
SYAMIL: Journal of Islamic Education Vol 13 No 3 (2025): SYAMIL: Journal of Islamic Education
Publisher : Pascasarjana Universitas Islam Negeri Sultan Aji Muhammad Idris Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21093/sy.v13i3.11935

Abstract

The integration of artificial intelligence is reshaping global education. This study systematically investigates the role of semi-supervised generative AI in transforming Islamic and moral education. This study aims to systematically investigate the role of semi-supervised generative artificial intelligence (AI) in transforming Islamic and moral education through a PRISMA-guided statistical systematic literature review. The increasingly widespread integration of AI tools such as ChatGPT, Gemini, DeepSeek, Agnes AI, and Cici has reshaped pedagogical practices, yet few studies have quantitatively examined their impact in faith-based education. A key issue addressed is the limited empirical understanding of how semi-supervised learning models mediate between human-guided moral instruction and AI-driven autonomous reasoning. Data were extracted from 38 peer-reviewed publications (2020–2025) across major databases and analyzed using statistical synthesis and meta-analysis. The results indicate a moderate positive effect size (d = 0.56) for generative AI in enhancing student engagement, critical thinking, and ethical reasoning in Islamic learning contexts. Tools such as ChatGPT and Gemini demonstrated the strongest pedagogical outcomes, while Agnes AI and Cici demonstrated unexplored potential. This study concludes that semi-supervised generative AI offers significant opportunities for pedagogical innovation and improved moral reasoning, although ethical supervision and the development of local AI models remain critical for sustainable implementation.
Transforming Islamic and Moral Education with Generative AI: A Statistical Systematic Review Budiyanto, Budiyanto; Al Matari, Ali Said; Adiyono, Adiyono; Dalimarta, Fahmy Ferdian
SYAMIL: Journal of Islamic Education Vol 13 No 3 (2025): SYAMIL: Journal of Islamic Education
Publisher : Pascasarjana Universitas Islam Negeri Sultan Aji Muhammad Idris Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21093/sy.v13i3.11935

Abstract

The integration of artificial intelligence is reshaping global education. This study systematically investigates the role of semi-supervised generative AI in transforming Islamic and moral education. This study aims to systematically investigate the role of semi-supervised generative artificial intelligence (AI) in transforming Islamic and moral education through a PRISMA-guided statistical systematic literature review. The increasingly widespread integration of AI tools such as ChatGPT, Gemini, DeepSeek, Agnes AI, and Cici has reshaped pedagogical practices, yet few studies have quantitatively examined their impact in faith-based education. A key issue addressed is the limited empirical understanding of how semi-supervised learning models mediate between human-guided moral instruction and AI-driven autonomous reasoning. Data were extracted from 38 peer-reviewed publications (2020–2025) across major databases and analyzed using statistical synthesis and meta-analysis. The results indicate a moderate positive effect size (d = 0.56) for generative AI in enhancing student engagement, critical thinking, and ethical reasoning in Islamic learning contexts. Tools such as ChatGPT and Gemini demonstrated the strongest pedagogical outcomes, while Agnes AI and Cici demonstrated unexplored potential. This study concludes that semi-supervised generative AI offers significant opportunities for pedagogical innovation and improved moral reasoning, although ethical supervision and the development of local AI models remain critical for sustainable implementation.
Analysis of the Implementation of Green Building Technology in Building Maintenance Kurniawan, Dimas Wahyu; Ratih, Silvia Yulita; Dalimarta, Fahmi F.; Susilo, Adhi
Jurnal Ilmiah Teknik Vol. 5 No. 1 (2026): Januari: Jurnal Ilmiah Teknik
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/juit.v5i1.2623

Abstract

Hospitals are resource-intensive facilities with continuous operations that result in high energy and water consumption, making the implementation of green building technology essential to improve environmental performance during the operational phase. Objective: This study aims to identify the energy, water, and material efficiency measures implemented at RSUD dr. Soeratno Gemolong, Sragen, and to evaluate the level of efficiency achieved based on EDGE (Excellence in Design for Greater Efficiencies) standards. Methods: The research employed an applied evaluative approach by collecting primary and secondary data through direct observation, interviews, documentation review (as-built drawings and material data), and literature review. The collected data were analyzed using the EDGE application and compared with EDGE benchmarks and relevant Indonesian regulations. Findings: The results indicate that baseline energy efficiency was 19.85%, slightly below the EDGE minimum requirement of 20%, but increased to 24.09% after targeted improvements such as reducing building envelope air infiltration and improving cooling system efficiency. Water efficiency reached 25.75%, and material efficiency achieved 34%, both exceeding the EDGE minimum standard. Implications: These findings demonstrate that EDGE-based evaluation can support maintenance-driven optimization strategies in hospital buildings and provide practical guidance for facility managers and policymakers in prioritizing high-impact efficiency interventions. Originality/Value: This study provides an integrated empirical assessment of energy, water, and material efficiency (EEM, WEM, MEM) in an operational public hospital, showing how targeted improvements can shift energy performance from near-compliance to compliant status within the EDGE framework.
Co-Authors Adhi Susilo Adiyono Adiyono Adiyono Al Matari, Ali Said Ali Said Al Matari Andono, Pulung N. Budiyanto Budiyanto Didi Kusaeri Doni Setiawan Faoziah, Nina Faoziyah, Nina Jaelani Jaelani Kurniawan, Dimas Wahyu Muzakki Mahdi Nugroho Susanto Pratama, Aziz Yulianto Pulung Nurtantio Andono Randi Dwi Wibisono Silvia Yulita Ratih Soeleman, Moch. A. Soeleman, Moch. Arief Sulistyo, Adi Zainal A. Hasibuan Zainal Arifin Hasibuan