Sweet Potato Pest Diagnosis Expert System (Ipomoea Batatas) with Forward Chaining Method and Certainty Factor

Abstract

Sweet potato (Ipomoea batatas) growth and development is influenced by biotic and abiotic factors. One of the biotic factors that influence it is a pest attack. Pests are organisms that cause direct damage to plants. Farmers need to make regular observations to minimize the occurrence of pest attacks. Regular observations help farmers find out early on pest populations on plants and can control them immediately. Pests on sweet potato plants are very diverse, therefore, to get the right diagnosis, farmers need to consult with experts where this is often an obstacle due to time and cost constraints. One way to facilitate the identification of these pests is to use a system that can provide conclusions based on the existing symptoms, this system is called an expert system. In this study, the authors build a web-based expert system application using the forward chaining method and certainty factor, while the software development method that the author uses is the waterfall method, and the software testing method uses the black box method. This research produces a web-based application. Based on testing, the application has been successful and runs well.