From Digital Administration to AI-Supported Governance: The Transformation Mechanism of Management Information Systems and Artificial Intelligence at UIN Kiai Ageng Muhammad Besari Ponorogo

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.