<![CDATA[The advancement of digital technology and internet penetration has opened wide opportunities for the development of Islamic educational applications. However, most existing Qur’an applications remain static and function merely as digitized texts without adaptive features. This study introduces TheRêst, an AI-based mobile application designed to enhance Qur’anic understanding through adaptive tafsir summarization, thematic sermon generation, and contextual sermon analysis. The development followed the Agile methodology, allowing iterative design, development, and testing processes. Key features were built using Natural Language Processing (NLP) and evaluated through black-box testing and usability testing with the System Usability Scale (SUS). Functional testing confirmed that core features—such as tafsir summarization and sermon generation—performed as expected, although challenges remained in response time and long-text accuracy. Usability testing involved 20 participants, including preachers, students of Islamic studies, and general Muslim users. Results showed an average SUS score of 79.25, categorized as “Excellent,” indicating strong user acceptance and satisfaction. Qualitative feedback highlighted the clarity of the interface and the usefulness of AI-generated content, while also noting the need for faster processing. This research contributes to the field of digital Islamic education by demonstrating the feasibility of integrating AI into Qur’an applications, thus providing innovative solutions for preachers and learners. Future work will focus on refining AI models, improving performance, and adding collaborative features. Overall, TheRêst presents a significant step toward creating adaptive, user-centered digital tools that support a deeper and more contextual engagement with the Qur’an.]]>
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