Article Per Year (5 Year)
p-Index From 2021 - 2026
3.544
P-Index
This Author published in this journals
All Journal Jurnal Mantik LEGAL BRIEF SOLID Jurnal Pemerintahan dan Keamanan Publik (JP dan KP) Jurnal Konstituen Al-Zayn: Jurnal Ilmu Sosial & Hukum Jurnal Kecerdasan Buatan dan Teknologi Informasi International Journal of Scientific Research Jurnal Perlindungan Masyarakat Bestuur Praesidium
Mujahidin
Institut Pemerintahan Dalam Negeri
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

Published : 24 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 24 Documents
Search

 1   2   3 
ARTIFICIAL INTELLIGENCE AS AN INSTRUMENT FOR LOCAL GOVERNMENT DECISION-MAKING: OPPORTUNITIES, RISKS, AND GOVERNANCE CHALLENGES Mujahidin
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.468

Abstract

This study aims to analyze artificial intelligence as an instrument for supporting local government decision-making, with particular attention to its opportunities, risks, and governance challenges. The study focuses on AI use in public services, licensing administration, and community-needs analysis, while emphasizing that AI must not replace the role of authorized public officials in governmental decision-making. This research uses a qualitative method with an exploratory-descriptive approach and conceptual governance framework development. Data were collected from secondary and documentary sources, including recent peer-reviewed journal articles, policy documents, institutional reports, regulatory materials, and scholarly works related to AI, automated decision-making, digital governance, local government administration, explainable AI, and public-sector ethics. The data were analyzed using thematic analysis by classifying findings into AI opportunities, algorithmic risks, human oversight, explainability, administrative accountability, institutional readiness, and ethical safeguards. The findings show that AI can support bureaucratic decisions by improving document screening, service-priority classification, licensing risk assessment, complaint analysis, eligibility recommendation, and identification of community needs. The study also finds that AI may create risks of algorithmic bias, opacity, privacy violation, automation bias, and administrative exclusion. The main contribution of this study is the formulation of a human-supervised AI decision-support framework consisting of data governance, AI-based administrative analysis, human verification, accountable decision-making, and citizen redress mechanisms.
GOVERNMENT BIG DATA GOVERNANCE MODEL TO IMPROVE THE EFFECTIVENESS OF INTEGRATED PUBLIC SERVICES Muhammad Kautsar; Mujahidin
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 4 No. 3 (2025): September 2025
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v4i3.470

Abstract

This study aims to analyze a government big data governance model for improving the effectiveness of integrated public services. The research focuses on inter-agency data integration, system interoperability, data security, and the use of public data in integrated service delivery. This study employs a qualitative method with an exploratory-descriptive approach and conceptual governance model development. Data were collected from secondary and documentary sources, including recent peer-reviewed journal articles, policy documents, institutional reports, digital government guidelines, regulatory materials, and scholarly works related to big data governance, data-driven government, interoperability, data security, and public-service innovation. The data were analyzed using thematic analysis by classifying findings into inter-agency data integration, system interoperability, data quality, data security, institutional coordination, collaborative governance, public-service effectiveness, and accountability. The findings show that integrated public services require more than digital applications or one-stop service portals. Effective integration depends on shared data standards, interoperable systems, secure data exchange, reliable data quality, and coordinated institutional responsibility. The study contributes by proposing a cross-sector government big data governance model consisting of institutional coordination, data integration, system interoperability, data quality assurance, data security, and collaborative service use. This model emphasizes that big data must be governed as a strategic public asset to improve service speed, accuracy, accessibility, transparency, and accountability.
CIVIL SERVANTS’ READINESS IN FACING THE IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE IN LOCAL GOVERNMENT BUREAUCRACY Marzuki; Mujahidin
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 1 (2026): January 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i1.471

Abstract

This study aims to analyze civil servants’ readiness in facing the implementation of artificial intelligence in local government bureaucracy. The study focuses on civil servants’ capacity, digital literacy, technological competence, organizational culture, and bureaucratic resistance to AI-based transformation. This research uses a qualitative method with an exploratory-descriptive approach and conceptual framework development. Data were collected from secondary and documentary sources, including recent peer-reviewed journal articles, policy documents, institutional reports, regulatory materials, and scholarly works related to AI adoption, digital transformation, civil-service competence, public-sector innovation, organizational culture, and bureaucratic resistance. The data were analyzed using thematic analysis by classifying findings into digital literacy, technological competence, organizational culture, leadership support, bureaucratic resistance, ethical awareness, and institutional support. The findings show that AI implementation in local government depends not only on technological infrastructure, but also on civil servants’ ability to operate digital systems, interpret algorithmic recommendations, evaluate data quality, and maintain public accountability. The study also finds that bureaucratic resistance may arise from fear of job displacement, loss of authority, weak technical confidence, rigid work culture, and lack of training. The main contribution of this study is the formulation of a human-centered AI readiness framework consisting of digital literacy, technological competence, adaptive organizational culture, ethical awareness, and institutional support. This framework emphasizes that civil servants are the key actors of successful AI transformation in local government bureaucracy.
Risk-Based Disaster Financing Governance: Assessing the Effectiveness of On-Call Funds, Village Funds, and Regional Budgets for Disaster Risk Reduction Mujahidin; Lalu Ahmad Murdhani
International Journal of Scientific Research Vol. 3 No. 01 (2026): March 2026
Publisher : Yayasan Hisnul Muslim Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62894/m8e6d162

Abstract

This study examines risk-based disaster financing governance by analyzing the effectiveness of on-call funds, village funds, and regional budgets in disaster risk reduction. The study is based on the argument that disaster financing should not be understood only as an emergency response mechanism, but also as a preventive governance instrument for reducing vulnerability, strengthening preparedness, and improving regional resilience. Using a qualitative case study approach, this research analyzes how disaster financing instruments are planned, allocated, coordinated, implemented, and evaluated at the local government level. Data were collected through in-depth interviews, field observations, and document analysis involving local disaster management agencies, regional planning agencies, financial management agencies, village governments, sectoral offices, disaster volunteers, and community representatives in disaster-prone areas. The findings show that on-call funds are effective in supporting rapid emergency response, but their contribution to long-term risk reduction remains limited when not supported by preventive financing. Village funds have significant potential for community-based mitigation and preparedness, yet their effectiveness depends on risk-informed village planning and technical capacity. Regional budgets can finance broader cross-sectoral risk reduction, but their implementation is often fragmented across institutions. This study proposes a risk-based disaster financing governance framework that connects risk assessment, fiscal planning, budget allocation, implementation, monitoring, and outcome-based accountability. The novelty of this study lies in shifting disaster financing analysis from reactive emergency expenditure toward preventive investment for disaster risk reduction and regional resilience.
Co-Authors Adyan Yanuar Ramadha Agus Gusnadi Agussalim Mad Arab Ahmad Robiansyah Awaly Ainaya Alfatihah Alfonsa Agustina Eka Cahyani Annisa Zahra Asha Mutiara Dimaputri Chendy Franklin Tan Dimaputri, Asha Mutiara Faris Risyadi Ferdi Wardana Gigih Nur Putra Pratama Lalu Ahmad Murdhani Lalu Ahmad Murdhani Lebinser Simatupang Marshela Manurung Marzuki Mitta Viska Maharani Mochamad Federico Azis Muhammad Dheva Aditama Muhammad Kautsar Muhammad Rivaldi Muhammad Shaufi Taqiyuddin Mulyadi, Muhamad Murdhani, Lalu Ahmad Selamet Dwi Purwantomo Syaefullah Zati Himmatil Aliyah