Rekomendasi Makanan Sehat Berbasis AI Menggunakan metode Forward Chaining dan NLP Stanza - Fedrick Fedrick; Hutagalung, Gita Noviani; Nasution, Nadya Balqis (Jurnal Ilmiah Teknik Informatika dan Komunikasi, 2025)
Artificial Intelligence (AI) is currently increasingly used in the health sector, including to help determine food choices that are appropriate for a person's physical condition. In this study, we developed a healthy food recommendation system that can read the symptoms felt by users through text, then provide food suggestions based on those conditions. This system uses natural language processing technology with the Stanza library, and applies the Forward Chaining method to draw conclusions from the symptoms given. Uniquely, this system does not require direct personal data, only from the description of symptoms typed by the user. We tested this system using 10 types of diseases and 40 common symptoms, taken from a total of 400 disease and symptom data in the knowledge base. As a result, the system is able to provide accurate recommendations, with a success rate of between 90% and 100%. With this capability, the system is expected to be a practical solution in helping people make healthier decisions regarding their daily food and nutrition.