<![CDATA[The purpose of this study is to help library users search for information more quickly, accurately, and contextually, and to provide a comprehensive understanding of the concepts and architecture of institutional repositories that use the Retrieval-Augmented Generation (RAG) method. This research adopts a Design Science Research (DSR) approach to address challenges in information retrieval arising from advances in artificial intelligence. The artifact developed is an artificial intelligence-based institutional repository system using the Retrieval-Augmented Generation (RAG) method. The research results regarding the implementation of building an institutional repository with the Retrieval-Augmented Generation (RAG) approach include the stages of identifying conventional repository issues from the past to the present, designing or conceptualizing an RAG-based system, the workflow of implementing RAG technology in institutional repositories, analysis of advantages, and implications for the academic environment. This study concludes that applying RAG to institutional repositories not only increases the efficiency of information search but also enriches the user experience in finding relevant, contextual knowledge. This research offers concrete and applicable solutions to improve the quality of library services in the digital era]]>
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