Expert System Identifying Peanut Plant Diseases Using a Web-Based Certainty Factor Method (Case Study: Hambapraing Village)

Peanuts (Arachis hypogaea L.) are one of the important agricultural commodities in Indonesia, especially in rural areas such as Hambapraing Village, East Sumba Regency. The productivity of these plants often decreases due to disease attacks that are difficult to recognize early due to the similarity of symptoms and limited access to experts. This research aims to develop a web-based expert system using the Certainty Factor method to assist farmers in identifying peanut plant diseases independently. The Certainty Factor method is used to handle uncertainty in the diagnosis process by providing a level of confidence in the user's chosen symptoms. The system was tested through 15 test scenarios and was able to achieve an accuracy level of 80%. These results show that the developed system can be a practical solution in detecting and managing plant diseases more quickly and precisely, especially in areas with limited access to agricultural experts.