Various species of Capsicum plants belong to the chili pepper genus, but five main species are most widely cultivated. Chili peppers are primarily grown for their fruits, which are important agricultural commodities. However, chili pepper productivity often declines due to pest and disease attacks. Because of this circumstance, a system that can help farmers promptly and precisely identify and manage plant diseases is required. In order to handle ambiguity in the reasoning process, this work aims to develop an expert system that uses the Certainty Factor (CF) method to identify infections in chili plants. The system is built on a knowledge base obtained from agricultural experts, covering five types of diseases and 18 main symptoms. The application is designed as a desktop-based software with a simple user interface and a maximum of seven selectable symptoms to improve diagnostic accuracy. A 10% error rate was obtained from testing 30 chili plant data samples using the Mean Absolute Percentage Error (MAPE), with three samples exhibiting diagnostic differences. This system is expected to enable farmers to moreĀ rapidly identify the types of diseases affecting chili plants and to obtain appropriate handling recommendations, thereby helping maintain agricultural productivity.
Copyrights © 2025