<![CDATA[The rapid advancement of artificial intelligence technology has expanded its applications across various domains, including customer service. Property owners often face challenges in promptly and consistently responding to inquiries from potential tenants, necessitating an automated information service solution. This study aims to implement the Retrieval-Augmented Generation (RAG) method in a chatbot to enhance customer service effectiveness in boarding house management. The research methodology involves developing a RAG-based chatbot prototype that integrates information retrieval from a knowledge database with the generative capabilities of a language model. Experimental results indicate that the application of the RAG method improves the relevance and accuracy of responses provided to prospective tenants. The RAG-based chatbot demonstrates faster response times compared to manual service, thereby reducing the workload on property owners. The implementation of RAG in the chatbot proves effective in automating customer service for boarding houses, offering added value to both property owners and potential tenants through fast, relevant, and easily accessible service.]]>
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