<![CDATA[Duta Wacana Christian University (UKDW), specifically Bureau 3 (BIRO 3), provides a variety of information services accessible through both online channels, such as Instagram, WhatsApp, and email, and offline methods. However, BIRO 3 has not yet implemented an FAQ Bot system, which means that frequently asked questions are still answered manually. This practice renders the question-and-answer process regarding campus information repetitive and time-consuming. This research aims to implement the RASA Open Source framework to develop an FAQ Bot system to automate the retrieval of information for frequently asked questions at BIRO 3, thereby enhancing the efficiency of its information services. The system was developed using RASA Open Source and implemented on the Telegram messaging platform. The evaluation was conducted through a two-fold approach. First, internal testing of the RASA model on the validation dataset yielded optimal results, achieving accuracy, precision, and F1-scores of 1.000. On the test data, the model demonstrated strong performance with an accuracy of 0.915, a precision of 0.928, and an F1-score of 0.912. Second, functional testing was performed by engaging users in predefined scenarios. This second phase of testing resulted in a functional accuracy of 95% based on 200 collected data points. The user testing results indicate that the FAQ Bot system was successfully developed and capable of achieving a functional accuracy rate of 95%. Despite its high performance, limitations were identified in the form of eleven false positive and false negative cases out of the 200 data points. This suggests that the model has not yet perfectly learned to comprehend all variations of user input. Therefore, recommendations such as expanding the training dataset and exploring modifications to the RASA Open Source framework are proposed to refine the system's capabilities, enabling it to handle all types of inquiries accurately.]]>
