Chatbot for Gastric Disease Consultation to Recommend a Healthy Diet Using KNN and NLP Methods - Hendrawaty; Azhar Azhar; Rafli Abdul Aziz (PT. Literasi Teknologi Informatika, 2025)
Gastric disease is one of the most common health problems and requires special treatment, including proper dietary arrangements. This research aims to design and build a healthy diet recommendation system using chatbots that utilize Natural Language Processing (NLP) and K-Nearest Neighbor (KNN) methods This system is designed to help people with gastric diseases by providing appropriate dietary recommendations based on the symptoms they are experiencing. In the design stage, the system identifies the symptoms mentioned by the user through a conversation with the chatbot. NLP is used to extract relevant information from the user's input text, while KNN is used to classify symptoms and provide appropriate dietary recommendations. The system was tested using a dataset that had been adjusted to cases of gastric diseases. The test results show that this chatbot system has a classification accuracy of 96.36%, with a confusion matrix that shows good performance in identifying symptoms and providing recommendations. The system is able to understand the context of the conversation well through NLP, while KNN provides accurate classification based on the available datasets. With these results, this system is expected to be an effective tool for gastric disease sufferers in managing their diet better and appropriately.