The Implementation of Natural Language Processing on Chatbot as Academic Information System: A Case Study of IC2IE 2024
Christian Nataniel Yosua Purba, Pratama Varian Andika Parulian, Ratna Widya Iswara, Ariawan Andi Suhandana, Risna Sari · 2024
The implementation of Natural Language Processing (NLP) in chatbots has significantly enhanced the efficiency and user experience of academic information systems. This paper presents a case study of the International Conference on Computing, Communication, and Information Engineering (IC2IE) 2024, exploring how NLP-driven chatbot can serve as a robust academic information system. By employing advanced NLP techniques, the chatbot effectively understands and processes user inquiries, providing accurate and timely information about the conference schedules, speakers, submission guidelines, etc. Accuracy testing demonstrated an overall performance of 84.533%, with perfect accuracy in the 0.75-1.0 similarity range and 96.15% accuracy in the 0.5-0.74 range. The findings suggest that integrating NLP in academic information systems can streamline operations and enhance communication within academic events.