<![CDATA[The development of a web-based chatbot service for Puskesmas presents a potential solution to improve the accessibility and efficiency of healthcare services. This research uses Flowise AI, a chatbot development platform that leverages machine learning technology to support dynamic information processing and provide accurate and relevant responses to users. Flowise AI is integrated with Langchain Retriever to further enhance dynamic information processing, ensuring accurate and relevant responses to users. Using the Rapid Application Development (RAD) methodology, the chatbot development follows a fast-paced cycle, enabling early prototyping and continuous user feedback. The chatbot is tested using Black Box Testing to verify functionality and System Usability Scale (SUS) to evaluate usability. The test results show that the chatbot is able to provide accurate responses to patient queries, especially on relevant health topics, with an SUS score of 75, which falls within the "good" category. This score reflects that the chatbot is easy to use and acceptable to users. This technology allows the chatbot to provide more accurate, relevant, and contextual responses to patient inquiries, while dynamically accessing information from various sources, thereby improving the efficiency and effectiveness of healthcare services.]]>
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