The increasing demand for efficient and accessible academic services has led higher education institutions to adopt innovative digital solutions. At STMIK Mulia Darma, students often experience delays and limited access to academic information due to manual service systems and limited staff availability. To address these challenges, this research proposes the development of an academic chatbot using Natural Language Processing (NLP) to automate and enhance student services. The chatbot is designed to understand and respond to student inquiries in Bahasa Indonesia, providing real-time information related to course schedules, registration procedures, tuition deadlines, and other academic matters. By integrating NLP with the institution’s academic information system, the chatbot delivers personalized and context-aware responses. The system was developed using a rule-based NLP model enhanced with intent classification and entity recognition techniques. Testing results indicate that the chatbot successfully answered more than 90% of user queries with acceptable response time and accuracy. This solution demonstrates the potential of NLP-powered chatbots to improve service efficiency, reduce administrative workload, and support the implementation of a smart campus ecosystem.
Batubara et al. (Thu,) studied this question.