Natural Language Processing for Interactive and Personalized Qur’anic Education - Agustina, Dinda; Maryam, Maryam; Marhamah, Siti (International Journal of Technology and Modeling, 2023)
The development of artificial intelligence technology, particularly Natural Language Processing (NLP), has opened significant opportunities for transforming Qur’anic learning methods. NLP, as a branch of AI focused on the interaction between computers and human languages, offers new approaches to understanding, analyzing, and teaching the text of the Qur’an in a more interactive and personalized manner. This article examines the utilization of NLP technology in the context of Qur’anic education, from the application of Arabic word morphology analysis to paragraph search systems based on meaning, and the development of virtual assistants capable of answering questions about the contents of the Qur’an. This approach not only enhances accessibility and learning efficiency but also strengthens semantic and contextual understanding of the holy verses. The study also highlights linguistic challenges in processing classical Arabic, as well as the importance of quality annotations and digital corpora. Through a literature review and case study implementation, this article demonstrates that the integration of NLP in Qur’anic learning is a strategic step to enrich Islamic education methods in the digital era, while also bridging the younger generation to the values of the Qur’an through relevant technology.