From Digital Administration to AI-Supported Governance: The Transformation Mechanism of Management Information Systems and Artificial Intelligence at UIN Kiai Ageng Muhammad Besari Ponorogo
M. Fadli Al AzhariHanh Dinh Thi MyKholis Al ArifuttaqiSulaiman Abdul Rasid
Aug 2026· Mapendis: Jurnal Manajemen Pendidikan Islam· Vol 4, pp. 66-77· 0 citations
TL;DR
The findings show that MIS integration through SIAKAD, SIMPEG, SIMKEU, LMS, SISTER, E-Office, and Single Sign-On has created a more connected institutional information infrastructure and implies that Islamic higher education institutions should prioritize interoperable information infrastructure, responsible AI governance, and institutional capacity before scaling AI-supported decision-making.
Abstract
This study addresses a governance problem often obscured by technology inventories: how an integrated Management Information System (MIS) serves as an institutional foundation for the emerging use of Artificial Intelligence (AI) in Islamic higher education governance. The literature has extensively examined MIS and AI as separate technologies, but provides less empirical explanation of what their integration changes in governance practice. This study therefore aims to examine (1) how MIS and AI are implemented and integrated at UIN Kiai Ageng Muhammad Besari Ponorogo, (2) how the integration contributes to institutional governance, and (3) what organizational and technological conditions enable or constrain the transition toward AI-supported governance. A qualitative case study was conducted using an in-depth interview with the Head of Information Technology and Database (TIPD), observation of digital services, and relevant institutional documentation. Data were analyzed using the interactive model of Miles, Huberman, and Saldaña through data condensation, data display, and conclusion drawing, supported by source and technique triangulation and member checking. The findings show that MIS integration through SIAKAD, SIMPEG, SIMKEU, LMS, SISTER, E-Office, and Single Sign-On has created a more connected institutional information infrastructure. AI, however, remains in an emerging stage: an NLP-based chatbot is under development, while predictive analytics, academic success and dropout prediction, and the smart-campus concept are identified as developing or prospective applications rather than fully operational systems. The central empirical contribution is that AI’s governance value depends on the maturity of the underlying MIS infrastructure: integration enables information to move from fragmented administrative records toward a shared data environment in which AI can potentially support anticipatory analysis and decision-making. Thus, the transformation mechanism is better understood as infrastructure integration → data consolidation → analytical capability → governance decision support, rather than simple technology adoption. The study implies that Islamic higher education institutions should prioritize interoperable information infrastructure, responsible AI governance, and institutional capacity before scaling AI-supported decision-making.
The study concludes that cultural transformation is not a by-product but a prerequisite of successful AI integration, and that change capacity, trust, and inclusive leadership are decisive.
Sadik M. Amr· World Journal of Advanced Re...· 0 citations
An exploratory literature review of the socio-technical issues involved in the adoption of GenAI tools in project documentation and governance and suggests a socio-technical conceptual framework that integrates these aspects into a unified view to inform people's understanding of responsible Human-AI collaboration in project settings.
Bela Lestari Dwireja, F. Abdalla, Yuhang Liu et al.· International journal of res...· 0 citations
A strong positive relationship was found between the use of AI and the four dimensions of corporate administration that were investigated, thereby suggesting that the proposed integrated framework could serve as a basis for developing a theory and organizational practice for the future.
Tulika Dutta Roy· International Journal of Mod...· 0 citations
The integration of Artificial Intelligence (AI) and digital platforms into public administration and private sectors is fundamentally reshaping governance structures worldwide. While these technologies offer substantial opportunities for efficiency and innovation, they simultaneously pose significant challenges to legal accountability, institutional legitimacy, social equity, and ecological sustainability. Despite a proliferation of policy initiatives, comprehensive evidence is lacking on how AI-driven governance concretely influences policy decision-making across diverse strategic sectors. This study employed a systematic literature review (SLR) methodology, following a structured screening and selection process. From an initial corpus, 45 peer-reviewed empirical and policy-oriented articles published between 2021 and 2026 were selected for in-depth analysis. A thematic synthesis approach was applied, categorizing the literature into four interconnected analytical pillars: (i) institutional transformation and regulatory governance, (ii) access, participation, and digital justice, (iii) innovation, competitiveness, and sustainable development, and (iv) ethics, risk mitigation, and policy legitimacy. The findings reveal that digital governance operates through four primary mechanisms: restructuring institutional procedures and oversight frameworks (law and public administration); enhancing access to resources, services, and citizen participation (agrarian and socio-cultural sectors); driving economic innovation and environmental sustainability (economic and resource management); and navigating ethical risks to maintain policy legitimacy (cross-cutting). A persistent gap was identified between technological adoption and the adaptive capacity of existing legal and regulatory institutions, particularly in addressing data governance, accountability, and inclusivity challenges. The SLR demonstrates that effective AI and digital platform governance demands a holistic, context-sensitive approach that actively balances efficiency with justice, innovation with accountability, and risk with public value. The study offers an integrative framework for policymakers and practitioners to navigate digital transformation complexities and establishes a robust foundation for future empirical research on policy decision-making in the digital era.
Generative artificial intelligence (GenAI) has emerged as a significant governance concern for higher education institutions, necessitating attention to responsible technology use, organisational capability, governance structures, resources, and ongoing oversight. This study investigates the institutionalisation of GenAI governance through a management-oriented qualitative document analysis of three documents from a focal higher education institution. Using the Technology–Organization–Environment (TOE) framework, the study identifies governance commitments articulated in the institution's AI policy and examines the technological, organisational, and environmental conditions influencing these commitments. The analysis employs a 13-construct TOE codebook to examine the institution's GenAI policy, the establishment of its responsible AI committee, and an earlier memorandum on AI in teaching and learning. The results demonstrate that the institution's governance response evolved through a progression from capability development to the establishment of formal governance structures and policy formalisation. Technological conditions created opportunities and practical requirements for GenAI governance, while organisational conditions—particularly leadership, structure, competence, resources, and readiness—were most extensively documented. Environmental conditions primarily defined regulatory and institutional boundaries. The findings indicate that GenAI governance becomes institutionalised not solely through policy formulation, but through organisational capacity to translate technological change into assigned responsibilities, coordinated structures, and sustained oversight. This study advances higher education management and AI governance by extending the TOE framework to institutional governance and by identifying a capability–structure–formalisation pattern for understanding how AI governance becomes embedded within university organisational arrangements.
Unknown authors· Journal of global economics,...· 0 citations
The digital transformation of public administration through computer-integrated technologies and artificial intelligence has become a key driver of effective, transparent, and citizen-oriented governance. This study aims to provide a comprehensive empirical assessment of the impact of digital transformation and AI readiness on government effectiveness worldwide. The analysis covers data from 190 countries. Government Effectiveness from the Worldwide Governance Indicators serves as the dependent variable, while the GovTech Maturity Index, E-Government Development Index (EGDI), Online Service Index, E-Participation Index, and Oxford Government AI Readiness Index are used as explanatory variables. The logarithm of GDP per capita (PPP) is included as a control variable. Spearman correlation and simple and multiple linear regression analyses reveal statistically significant positive relationships between all digital indicators and government effectiveness. The strongest effects are observed for EGDI (β = 0.820) and the Oxford Government AI Readiness Index (β = 0.759). After controlling for economic development, digital factors remain significant predictors, with adjusted R² values ranging from 0.693 to 0.733. Based on these findings, the DT-CIT-AI (Digital Transformation–Computer-Integrated Technologies–Artificial Intelligence) model is proposed, integrating technological infrastructure, intelligent systems, digital citizen participation, and governance effectiveness. The results confirm that investments in digital technologies and artificial intelligence substantially enhance public administration performance regardless of a country's level of economic development.
H. Kazarian, Serhiy Gryvko, Dmytro Voronets et al.· Aposta: Revista de Ciencias...· 0 citations
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