Implementasi Smart Learning Berbasis Hybrid Chatbot Menggunakan Metode TF-IDF dan Fuzzy Matching untuk Meningkatkan Literasi Digital Mahasiswa
Keywords:
Smart Learning, Hybrid Chatbot, TF-IDF, Fuzzy Matching, Digital LiteracyAbstract
The rapid advancement of digital technology has encouraged higher education institutions to adopt innovative learning media that support students' digital literacy. One of the promising technologies is an educational chatbot that provides interactive and responsive learning assistance. This study aims to implement a Smart Learning system based on a Hybrid Chatbot using Term Frequency–Inverse Document Frequency (TF-IDF) and Fuzzy Matching to support digital learning. This research employed the Research and Development (R&D) method using the ADDIE model, consisting of Analysis, Design, Development, Implementation, and Evaluation stages. The system was developed using Python and the Flask framework, while the knowledge base consisted of 400 question–answer pairs organized into ten knowledge categories. Data analysis was conducted through text preprocessing, Rule-Based Matching, TF-IDF vectorization, Cosine Similarity, and Fuzzy Matching, followed by system performance evaluation. The results indicate that the proposed Hybrid Chatbot is capable of recognizing various user query patterns, including different sentence structures and typographical errors, thereby providing more relevant responses than conventional exact matching. The developed Smart Learning application offers an interactive, adaptive, and accessible digital learning environment that can support students' independent learning and contribute to the implementation of technology-enhanced learning in higher education.
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