<![CDATA[Rice plant diseases are closely linked to pest-related factors, which constitute a primary cause of reduced crop yields in Indonesia. This study aims to develop a web-based monitoring and disease risk prediction system to assist farmers in the early detection of diseases based on environmental conditions and observable symptoms. The system was developed using the Waterfall methodology and incorporates a forward-chaining inference engine for decision-making; data inputs were derived from interviews with agrotechnology experts and literature reviews from BBPSI Padi (2024). The system was built using PHP and MySQL, running on an XAMPP web server. Risk predictions are generated based on parameters such as air temperature, relative humidity, and rainfall. To ensure ease of access for farmers, the system was designed without requiring user registration or login. The results demonstrate that the system facilitates practical and easily understandable monitoring of field conditions, preliminary disease diagnosis, and risk prediction. It is expected that this system will enable farmers to take early preventive measures, thereby mitigating the risks of crop damage, yield reduction, and total crop failure.]]>
Copyrights © 2026
