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All Journal Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Scientia Jurnal Multidisiplin West Science West Science Interdisciplinary Studies Jurnal Geosains West Science West Science Interdisciplinary Studies The Eastasouth Journal of Information System and Computer Science Science Information System and Technology West Science Nature and Technology
Hanifah Nurul Muthmainah
Universitas Siber Muhammadiyah
Humanities Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Environmental Science Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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The Influence of Data Quality and Machine Learning Algorithms on AI Prediction Performance in Business Analysis in Indonesia Loso Judijanto; Donny Muda Priyangan; Hanifah Nurul Muthmainah; I Wayan Jata
The Eastasouth Journal of Information System and Computer Science Vol. 1 No. 02 (2023): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v1i02.182

Abstract

This research investigates the intricate relationships among AI prediction performance, business analysis, data quality, and machine learning algorithms within the manufacturing sector in Indonesia. Through structural equation modeling analysis, the study explores the impact of these variables on one another, shedding light on the dynamics that contribute to successful AI adoption and business decision-making. The findings underscore the pivotal role of data quality in influencing AI prediction performance and machine learning algorithms, ultimately shaping the effectiveness of business analysis. The results provide practical insights for manufacturing companies seeking to optimize their data management practices and harness the potential of advanced technologies for strategic decision-making.
Bibliometric Analysis AI-Based Decision Analytics Loso Judijanto; Hanifah Nurul Muthmainah
West Science Information System and Technology Vol. 4 No. 02 (2026): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v4i02.3096

Abstract

The rapid advancement of artificial intelligence (AI) has transformed decision-making processes across various domains by enabling data-driven insights, predictive capabilities, and intelligent automation. This study aims to examine the development, intellectual structure, and emerging trends of research on AI-based decision analytics through a bibliometric analysis approach. Data were collected from the Scopus database using relevant search terms related to artificial intelligence and decision analytics. The study applies bibliometric techniques, including performance analysis, citation analysis, co-authorship analysis, keyword co-occurrence analysis, thematic evolution analysis, and density visualization using VOSviewer. The findings indicate that artificial intelligence, machine learning, deep learning, and clinical decision support systems represent the dominant research themes shaping this field. Highly cited studies demonstrate increasing scholarly attention toward ethical considerations, explainability, transparency, and trust in AI-driven decision systems. The collaboration analysis reveals that research development is supported by extensive international networks, with countries such as Germany, the United States, India, and China serving as influential contributors. Furthermore, the temporal analysis indicates a shift from algorithm-focused research toward human-centered and responsible AI applications. This study contributes to the literature by providing a comprehensive mapping of AI-based decision analytics research and identifying future directions related to explainable AI, trustworthy decision systems, and interdisciplinary applications across healthcare, business, and other complex decision environments.
Information Technology Governance Research in the Digital Era: A Scopus-Based Bibliometric Analysis Loso Judijanto; Hanifah Nurul Muthmainah; Joni Wilson Sitopu
The Eastasouth Journal of Information System and Computer Science Vol. 4 No. 01 (2026): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v4i01.1206

Abstract

This study aims to map and analyze the global research landscape of information technology (IT) governance in the digital era through a bibliometric approach. Data were retrieved from the Scopus database and analyzed using VOSviewer software to examine co-authorship patterns, institutional collaborations, country contributions, keyword co-occurrence structures, and citation impact. The co-authorship network reveals that this segment of the literature is dominated by a single, tightly interconnected research team rather than a broad community of independent contributors, while institutional collaboration remains sparse and is bridged only by a public-administration-affiliated unit connecting a geospatial land-governance research community with a cross-border, financial-technology-oriented data-governance community. At the country level, China, the United States, the United Kingdom, India, and Indonesia emerge as the principal hubs of international collaboration, supported by extensive participation from Europe, the Middle East, and Southeast Asia, indicating that IT governance research constitutes a genuinely global, multipolar undertaking. The keyword co-occurrence analysis shows that the field is organized around four interconnected clusters covering cybersecurity and blockchain-based governance, artificial intelligence and digital transformation, big data-driven decision-making, and e-government and ICT-based public governance, with digital governance and information management forming the field's conceptual core. The citation analysis further shows that the field's intellectual foundation is anchored in the digital-era governance model and its subsequent extension toward artificial intelligence, alongside diverse contributions from e-government adoption, geospatial data integration, and data-driven policymaking research. Taken together, these findings indicate that IT governance research has developed into a rapidly expanding, technology-driven field, with growing convergence toward artificial intelligence, cybersecurity, and data governance as its emerging frontiers.
Co-Authors Abrar Hiswara Aditya Djaini Agi Nanjar Agstriningtyas, Alvionitha Sari Ahmad Muktamar B Andi Haslinah Andi Muh Akbar Saputra ARIEF BUDI PRATOMO Arnes Yuli Vandika Astrid Napita Sitorus Devi Susiati Dewantara, Rizki Dianta Mustofa K. Donny Muda Priyangan Eko Sudarmanto Eri Mardiani Farida Arinie Soelistianto Fauzi Fauzi Febrian, Wenny Desty Fildansyah, Rully Fryda Fatmayati Gogor Christmass Setyawan Hakim, Nur Hamzali, Said Hidayat, Deddy Jata, I Wayan Joni Wilson Sitopu Judijanto, Loso Khamaludin Khamaludin Khamaludin, Khamaludin Kristiono, Natal Loso Judijanto Mahmudin Mahmudin Mahmudin Mahmudin, Mahmudin Mayasari, Nanny Mislan Sihite, Mislan Moh. Erkamim Mohammad, Wily Muh. Aniar Hari Swasono Muhammad Hazmi Nabilah, Annisa Nurul Nanjar, Agi Nanny Mayasari Nur Hakim Nurnaninsih A Purnamasari, Etika Rifky Lana Rahardian Rully Fildansyah Said Hamzali Salfin Saputri, Dwi Yuniasih Siti Agus Kartini Sri Widiastuti Sri Widiastuti, Sri Sriyeni, Yesi Supriandi Supriandi Susatyo Adhi Pramono, Susatyo Adhi Syam Gunawan Syam Gunawan Tobias Duha Wibowo, Gentur Wahyu Nyipto Widyatmoko Widyatmoko Wily Mohammad Zunan Setiawan