The increasing prevalence of spiritual crises among university students, coupled with the limited accessibility of Islamic counseling services, calls for innovative technological solutions. This study explores the development of an Islamic counseling chatbot utilizing Natural Language Processing (NLP) for early detection of spiritual crises in Muslim students. It analysing the conceptual framework, technical requirements, and implementation strategies for developing an NLP-based Islamic counseling chatbot system for early spiritual crisis detection. This qualitative research employs a systematic literature review approach, analysing 127 relevant publications from 2018 to 2024 sourced from Scopus, Web of Science, PubMed, and Islamic databases. Thematic analysis was conducted using NVivo 12 to identify key themes and patterns. Five core themes emerged: (1) Technological architecture integrating Islamic principles with NLP algorithms, (2) Specific indicators of spiritual crisis among Muslim students, (3) Culturally sensitive conversational patterns, (4) Ethical considerations in AI-assisted Islamic counseling, and (5) Implementation challenges and solutions. The proposed chatbot framework incorporates Qur’anic verses, hadith references, and Islamic psychology concepts into machine learning algorithms. The NLP-based Islamic counseling chatbot demonstrates significant potential for early detection and intervention in spiritual crises among university students. However, successful implementation requires careful consideration of Islamic ethics, cultural sensitivity, and technical resilience.
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