OPTIMIZATION IN ZAKAT MANAGEMENT THROUGH THE DEVELOPMENT OF A CHATBOT-BASED MOBILE APPLICATION

The growing awareness of zakat, infaq, and sadaqah (ZIS) in Indonesia calls for intelligent and transparent management systems. This study proposes a chatbot-based mobile application integrated with the SECI knowledge management model to optimize ZIS management and distribution. Using the waterfall software development model, the research includes requirement analysis, system design, chatbot implementation, and validation. The decision-tree-based chatbot enables interactive and personalized guidance for muzakki, while the SECI framework ensures structured knowledge sharing among zakat institutions. Functional and compatibility testing show that the system operates reliably on Android version 10 and above, with intent classification accuracy reaching 92 percent. The findings demonstrate that combining intelligent interaction and structured knowledge management improves transparency, operational efficiency, and institutional learning in digital zakat systems. The proposed framework provides both theoretical and practical contributions to advancing socio-economic management through mobile technology