Reorienting Muraqabah for AI-Driven Teacher Performance Monitoring: Exploring Quality Assurance Transformations within Islamic Education

(Reorientasi Konsep Muraqabah dalam Monitoring Kinerja Guru Berbasis AI: Studi Eksploratif Terhadap Transformasi Penjaminan Mutu di Institusi Pendidikan Islam)

Abstract

The integration of Artificial Intelligence (AI) in Islamic education demands a balance between technical efficiency and spiritual values to prevent dehumanization in performance management. This qualitative study employs an exploratory approach and a systematic literature review to examine the reorientation of the muraqabah concept within a teacher performance monitoring system based on the YOLOv8 algorithm. Research findings indicate that technically, YOLOv8 is highly effective in identifying classroom interactions with a mean Average Precision (mAP) of 85.8%, significantly reducing subjective bias found in traditional methods. Philosophically, the reorientation of muraqabah transforms the perception of digital surveillance from a privacy threat into a means of achieving the state of ihsan. This synergy is proven to mitigate AI-induced educational anxiety and strengthen a sustainable quality culture through intrinsic-transcendental responsibility. The study concludes that a hybrid monitoring model combining algorithmic precision with spiritual reflection is the key to transforming quality assurance in future Islamic educational institutions.