Web-Based Expert For Rice Disease Diagnosis Using A Hybrid Certainty Factor And Forward Chaining Method And Ai Integration
Sistem Pakar Diagnosis Penyakit Padi Berbasis Web Dengan Metode Hybrid Certainty Factor Dan Forward Chaining Serta Integrasi AI
DOI:
https://doi.org/10.21070/ups.10248Keywords:
Rice Plant Diseases, Expert System, Forward Chaining, Certainty Factor, AI IntegrationAbstract
Rice plant diseases are one of the main factors causing decreased productivity and harvest quality, while diagnosis in the field still relies on farmers’ experience, leading to potential inaccuracies due to similar symptoms. This study aims to develop a web-based expert system for rice disease diagnosis using a hybrid Forward Chaining and Certainty Factor method with Artificial Intelligence integration for solution recommendations. Forward Chaining is used to determine candidate diseases based on selected symptoms, while Certainty Factor calculates the confidence level of diagnosis under uncertainty conditions. The system was developed using the Expert System Development Life Cycle (ESDLC) and tested through black-box testing. The results show that the system can generate accurate diagnoses, confidence values, and relevant handling recommendations. The proposed system supports early and independent disease diagnosis effectively while maintaining AI as a supporting component rather than a decision maker.
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