<![CDATA[The rapid development of Artificial Intelligence has created new opportunities to improve learning processes in higher education. One of the emerging technologies is the educational chatbot, which can provide interactive, flexible, and immediate assistance to students during independent study activities. In database courses, many students experience difficulties in understanding abstract concepts such as normalization, table relationships, keys, entity relationship diagrams, and Structured Query Language (SQL). Limited classroom time and differences in student learning pace often make it difficult for lecturers to provide continuous support for all learners. This study aims to implement a chatbot-based learning assistant to support students’ understanding of database concepts. The research employed an applied research approach with a system implementation design. Data were collected through observation, questionnaires, and documentation, while the system was developed using the Waterfall model consisting of requirement analysis, design, implementation, testing, and deployment stages. The results indicate that the chatbot was successfully implemented as a web-based learning tool and received positive evaluations from students in terms of usefulness, ease of use, accessibility, response quality, and support for conceptual understanding, with an overall mean score of 4.33 in the very good category. The chatbot helped students obtain immediate explanations, review course materials, and better understand important database topics. The study concludes that chatbot technology can function as an effective supplementary learning assistant that complements traditional teaching and creates a more flexible learning environment in higher education.]]>
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