IMPLEMENTATION OF CHATBOT USING TEMPLATE MATCHING AND ARTIFICIAL INTELLIGENCE METHOD TO INCREASE STUDENT READING INTEREST

Student reading interest in Indonesia remains relatively low, which impacts the utilization of library resources. One contributing factor is limited access to fast and easy information, making students reluctant to seek references beyond academic requirements. This study aims to develop a library chatbot using the Template Matching method integrated with ChatGPT artificial intelligence. The chatbot is designed to deliver interactive, quick, and relevant information services. System development followed the Waterfall method, while evaluation employed black-box testing and a Likert scale survey to measure user satisfaction. Results showed an average score of 83.12%, categorized as “Strongly Agree.” These findings indicate that the chatbot effectively facilitates access to library information and enhances user satisfaction. Moreover, it has the potential to increase student engagement with library services and contribute positively to improving reading interest. Future research should explore broader applications and long-term impacts of chatbot-based information systems.