Web-Based Intelligent Technology for Diagnosing Rice Plant Diseases to Enhance Food Security in South Kalimantan

The development of a web-based expert system is crucial for diagnosing and addressing diseases in rice plants, which are a vital sector in global food security, economics, and environmental sustainability. The research was conducted in the region of South Kalimantan Province. This research aims to analyze variables of rice plant diseases, utilizing decision trees for identification, categorizing diseases based on symptoms, and developing a web-based expert system for detecting rice plant diseases, with the hope of providing benefits in enhancing food security, providing agricultural policy data, and demonstrating the application of technology for sustainability and efficiency in the agricultural sector. The results of the expert system, using $100 \%$-unit testing with 200 data samples, passed, while manual testing with 50 data samples achieved an accuracy rate of $\mathbf{9 6 \% o r}$ the model experienced misprediction of diseases based on symptoms four times.