cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Naety
Contact Email
jurnalmedicom@iocscience.org
Phone
+6281381251442
Journal Mail Official
jurnalmedicom@iocscience.org
Editorial Address
Perumahan Romeby Lestari Blok C, No C14 Deliserdang, Sumatera Utara, Indonesia
Location
Unknown,
Unknown
INDONESIA
Jurnal Teknik Informatika C.I.T. Medicom
Published by Institute of Computer Science
ISSN : 23378646     EISSN : 2721561X     DOI : -
Core Subject : Science,
Computer Science & IT
The Jurnal Teknik Informatika C.I.T a scientific journal of Decision support sistem , expert system and artificial inteligens which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 143 Documents
 11   12   13   14   15 
A Conceptual Framework for Autonomous AI Governance in Smart Digital Ecosystems Bambang Saras Yulistiawan
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 3 (2023): July: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid advancement of autonomous Artificial Intelligence (AI) technologies has significantly transformed smart digital ecosystems across sectors such as smart cities, healthcare, fintech, autonomous transportation, Internet of Things (IoT), and Industry 4.0. While autonomous AI offers substantial benefits in automation, efficiency, and intelligent decision-making, its increasing adoption also creates complex governance challenges related to algorithmic bias, lack of transparency, cybersecurity threats, privacy violations, accountability ambiguity, and long-term societal risks. This study aims to develop a conceptual framework for autonomous AI governance in smart digital ecosystems by integrating ethical, technical, regulatory, adaptive, and human-centered governance dimensions into a unified governance architecture. This study employs a qualitative conceptual research approach using theory-building methodology and literature synthesis. Data were obtained from academic journals, conference proceedings, AI governance reports, international regulations, policy documents, and institutional publications related to autonomous AI, responsible AI, cybersecurity, and digital governance. The analysis was conducted using systematic literature review, thematic analysis, comparative framework analysis, conceptual mapping, and governance modeling techniques. The findings indicate that autonomous AI governance requires a multidimensional and interconnected governance structure capable of addressing ethical, legal, technical, organizational, and sustainability challenges simultaneously. The proposed framework consists of six governance dimensions: ethical governance, regulatory governance, technical governance, data governance, adaptive governance, and human-AI collaboration governance. These dimensions collectively support fairness, transparency, accountability, cybersecurity, privacy protection, ecosystem resilience, and human oversight within autonomous AI environments. This study concludes that integrated and adaptive governance mechanisms are essential for ensuring responsible, transparent, secure, and sustainable AI implementation in smart digital ecosystems while supporting trustworthy and resilient digital transformation.
Toward an Integrated Intelligent Data Governance Architecture for Decision-Centric Digital Systems Bambang Saras Yulistiawan
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 3 (2023): July: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid advancement of artificial intelligence (AI), big data analytics, cloud computing, Internet of Things (IoT), and autonomous digital technologies has transformed modern digital ecosystems into highly interconnected and decision-centric environments. However, the widespread adoption of intelligent systems has also introduced significant governance challenges, including fragmented data governance, cybersecurity risks, interoperability limitations, privacy concerns, algorithmic bias, lack of transparency, and weak accountability mechanisms. Existing governance frameworks often operate independently across data governance, AI governance, cybersecurity, and decision-support systems, making them inadequate for managing dynamic and intelligent digital infrastructures. This study aims to propose an integrated intelligent data governance architecture that supports adaptive, secure, transparent, and decision-centric digital systems. This study employs a qualitative-conceptual methodology using Design Science Research (DSR), Systematic Literature Review (SLR), and framework development approaches. Secondary data were collected from scientific journals, conference proceedings, governance frameworks, industry reports, and international standards such as ISO, OECD AI Principles, NIST AI RMF, GDPR, COBIT, and DAMA-DMBOK. Data analysis was conducted using thematic analysis, comparative analysis, architectural analysis, and governance layer modeling. The findings reveal that intelligent digital ecosystems require integrated governance mechanisms combining data governance, AI governance, cybersecurity, explainable AI, interoperability, decision intelligence, and adaptive feedback systems. The proposed architecture consists of seven interconnected layers that collectively improve governance transparency, accountability, operational resilience, digital trust, and decision quality. The study concludes that integrated intelligent governance architectures are essential for supporting sustainable, secure, and trustworthy digital transformation in modern AI-driven environments.
A Unified Theoretical Model of AI-Driven Governance for Adaptive Digital Transformation Bambang Saras Yulistiawan
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 2 (2024): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid advancement of artificial intelligence (AI), Internet of Things (IoT), cloud computing, big data analytics, and autonomous systems has accelerated digital transformation across various sectors, creating increasingly interconnected and intelligent digital ecosystems. However, the widespread adoption of AI technologies also generates complex governance challenges related to transparency, accountability, cybersecurity, data privacy, interoperability, and ethical compliance. Existing AI governance frameworks remain fragmented, sector-specific, and insufficiently integrated to address the adaptive and dynamic nature of modern digital environments. Therefore, this study aims to develop a unified theoretical model of AI-driven governance for adaptive digital transformation. This research employs a qualitative conceptual approach using a systematic and integrative literature review methodology. Relevant literature, governance frameworks, policy documents, and digital transformation studies were analyzed through thematic analysis and conceptual synthesis to identify the core dimensions of effective AI governance. The study integrates governance principles, ethical considerations, organizational structures, and technological mechanisms into a comprehensive multi-layered framework. The findings of the study propose a unified AI governance model consisting of interconnected dimensions, including transparency and explainability, accountability mechanisms, data governance and privacy, cybersecurity resilience, interoperability across systems, and adaptive feedback mechanisms. Compared to existing governance models, the proposed framework provides a more integrated and adaptive approach by bridging fragmented governance perspectives into a single coherent structure. In conclusion, the proposed unified AI governance model contributes theoretically to governance and AI ethics literature while providing practical guidance for governments, organizations, and technology developers in implementing responsible, transparent, and sustainable AI governance systems to support adaptive digital transformation.

Page 15 of 15 | Total Record : 143

 11   12   13   14   15 

Filter by Year

2018 2026


Reset
Filter By Issues
All Issue Vol 18 No 1 (2026): March: Intelligent Decision Support System (IDSS) Vol 17 No 6 (2026): Computer Science Vol 17 No 5 (2025): Intelligent Decision Support System (IDSS)- INPRESS Vol 17 No 4 (2025): Intelligent Decision Support System (IDSS) Vol 17 No 3 (2025): July: Intelligent Decision Support System (IDSS) Vol 17 No 2 (2025): May: Intelligent Decision Support System (IDSS) Vol 17 No 1 (2025): March: Intelligent Decision Support System (IDSS) Vol 16 No 6 (2025): January : Intelligent Decision Support System (IDSS) Vol 16 No 5 (2024): November : Intelligent Decision Support System (IDSS) Vol 16 No 4 (2024): September: Intelligent Decision Support System (IDSS) Vol 16 No 3 (2024): July: Intelligent Decision Support System (IDSS) Vol 16 No 2 (2024): May: Intelligent Decision Support System (IDSS) Vol 16 No 1 (2024): March: Intelligent Decision Support System (IDSS) Vol 15 No 6 (2024): January : Intelligent Decision Support System (IDSS) Vol 15 No 5 (2023): November : Intelligent Decision Support System (IDSS) Vol 15 No 4 (2023): September : Intelligent Decision Support System (IDSS) Vol 15 No 3 (2023): July: Intelligent Decision Support System (IDSS) Vol 15 No 2 (2023): May: Intelligent Decision Support System (IDSS) Vol 15 No 1 (2023): March: Intelligent Decision Support System (IDSS) Vol 14 No 2 (2022): September: Intelligent Decision Support System (IDSS) Vol 14 No 1 (2022): March: Intelligent Decision Support System (IDSS) Vol 13 No 2 (2021): September: Intelligent Decision Support System (IDSS) Vol 13 No 1 (2021): March: Intelligent Decision Support System (IDSS) Vol 12 No 2 (2020): September: Intelligent Decision Support System (IDSS) Vol 12 No 1 (2020): March: Intelligent Decision Support System (IDSS) Vol 11 No 2 (2019): Informatik Vol 11 No 1 (2019): Informatika Vol 10 No 2 (2018): Informatika More Issue