<![CDATA[The low literacy of the Qur’an in the digital era is not solely due to limited access to sacred texts, but mainly to the absence of interactive, adaptive, and contextual interpretation learning platforms. This study conducted a conceptual design analysis and epistemological framework of MAQTAF (Qur’an Analysis and Interactive Interpretation Engine), an artificial intelligence (AI)-based innovation designed to strengthen the ummah’s understanding of the Qur’an. Using a qualitative approach based on literature reviews, this study does not develop or test functional prototypes. Still, it rather systematically describes the design architecture, the operational mechanisms of AI (including natural language processing with retrieval-augmented generation and adaptive learning through collaborative filtering), and the integration of the maqāṣid al-syarī'ah classifier as an ethical filter. The findings of the study present three novelties: (1) the simultaneous combination of verse/interpretation analysis, interactive adaptive learning, and thematic multimedia content, an integration that is not found on existing linear platforms; (2) The operationalization of maqāṣid as a supervised learning-based classifier that evaluates the output of tafsir into five dimensions ḥifẓ al-dīn, al-nafs, al-'aql, al-nasl, al-māl; and (3) the formulation of AI as an epistemological support tool rather than a substitute for scientific authority through a three-layer validation mechanism (data sources, algorithms, and scholarly supervision). As a conceptual design study, MAQTAF offers an ex ante framework that requires future empirical validation through design-based research and expert assessment. Thus, this research contributes to strengthening digital Islamic literacy and encourages a deeper understanding of the Qur’an, which is ethically responsible and relevant to the context of modern society.]]>
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