Penerapan Sistem Pakar Diagnosa Penyakit Tanaman Buah Naga Berbasis Web Menggunakan Metode Certainty Factor Application Of A Web-Based Dragon Fruit Plant Disease Diagnosis Expert System Using Certainty Factor Method

Abstract

Dragon fruit plants are one of the agricultural commodities that are widely cultivated because they have a fairly high market value. However, in practice, these plants are susceptible to various types of diseases that can affect growth and crop yield. The lack of farmers' knowledge in recognizing disease symptoms early as well as limited access to experts becomes an obstacle in proper handling.

This study aims to develop a web-based expert system capable of assisting the disease diagnosis process in dragon fruit plants. This system utilizes the Certainty Factor method to process the level of confidence in a disease based on symptoms selected by the user. The system development process is carried out by compiling a knowledge base in the form of disease data, symptoms, and rules obtained from references and related experts.

The resulting application is equipped with data processing features, as well as the presentation of diagnostic results in an informative manner, including the type of disease, certainty value, and recommended treatment. System testing shows that the application is capable of providing diagnostic results that are quite accurate and consistent with expert analysis. With this system, it is expected that users, especially farmers, can more easily identify dragon fruit plant diseases independently and take faster and more appropriate treatment measures.

System testing was carried out using the black box testing method and expert validation. Based on the test results on 30 case data, the system produced an accuracy rate of 86.67% compared to expert diagnosis. The certainty factor values produced ranged from 0.6 to 0.9, indicating a medium to high level of confidence.