Development of a Chatbot Education System for Protected Marine Animals in Papua Using the Large Language Models Method

Alfikran Anang, Anggun Maimunah, Annisa Iriani Tawainella, Suhardi Aras

Abstract


The research aims to raise awareness about protected marine species in Papua through a chatbot providing accessible information. This strengthens public and student understanding of marine conservation. Methods include problem analysis, literature study, data collection, and system analysis and design using PyMuPDF and a Large Language Model (LLM). Data from scientific journals, books, e-books, and websites is processed through chunking and embedding to create vector representations. The FITZ library stores these vectors, enabling the chatbot to find similarities and provide relevant answers. Results show the chatbot accurately delivers information on Papua's protected marine animals. Testing with BERTScore indicated a high semantic correlation between chatbot responses and reference data. User satisfaction surveys reveal positive contributions to understanding marine conservation. The chatbot is relevant and satisfying, though performance and functionality could be improved with advanced technology. Further research should enhance data quality and answer consistency to better meet user needs.

Keywords


Chatbot, Protected Sea Animals, Papua, Large Language Models, BERTScore.

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References


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DOI: https://doi.org/10.30596/jcositte.v6i1.20677

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