<![CDATA[The agricultural census query builder system has two modes: a query builder mode with an interface that facilitates the selection of tables, columns, and query criteria, and an SQL programming mode for executing SQL queries. The system provides a list of queries for basic anomaly checking nationwide, but advanced and unique anomaly checking for each work unit requires writing SQL queries from scratch, which is inefficient. This research developed a chatbot application that translates user queries into SQL queries for data anomaly checking. This chatbot uses the Large Language Model (LLM) GPT-4o. The chatbot application development uses the Rapid Application Development (RAD) model for rapid system development. Black Box Test and System Usability Test with System Usability Scale (SUS) show the results as expected by the user, with an average SUS score of 84.17 which indicates the chatbot application is acceptable.]]>
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