<![CDATA[The limited human resources in dental clinics often lead to delays in responding to patients' initial consultations, potentially reducing service quality and patient satisfaction. The advancement of Artificial Intelligence (AI) has encouraged the adoption of chatbots based on Natural Language Processing (NLP) to improve information service efficiency. This study aims to implement a chatbot using the Bidirectional Encoder Representations from Transformers (BERT) model to enhance consultation efficiency at the dental clinic of drg. Fahmi Nurdin. The system development method used is Agile, with stages including requirement analysis, user interface design, model training, and chatbot implementation. The dataset consists of 49 tags (topics) and 490 patterns (questions), formatted in JSON, and used to train the BERT model for intent classification and response generation. Evaluation results show that the chatbot can provide relevant and accurate responses, accelerating the initial consultation process. This implementation is expected to help overcome human resource limitations, improve service quality, and strengthen patient trust in the clinic's services.]]>
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