This research develops a passage retrieval model for a Question Answering (QA) application in the Indonesian language, focusing on a specific domain. The model leverages BERT embedding techniques and the Faiss index to enhance the efficiency and accuracy of finding answers to user queries, with a particular focus on a text corpus related to Universitas Perjuangan Tasikmalaya. The evaluation was conducted on 80 questions, encompassing various informational aspects within the corpus. Results indicate an average execution time of 0.23 seconds per question and a total processing time of 18.8 seconds for all queries, achieving an accuracy rate of 43.75%. Accuracy was generally higher when the questions contained terms that exactly matched those in the corpus. While the initial findings are promising, the accuracy remains suboptimal and warrants further improvement. Potential areas for optimization include employing alternative embedding techniques, refining passage formation methods, and enhancing search performance using a cross-encoder. This research contributes to accelerating the retrieval process and improving the relevance of results for QA applications within specific domains.
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