Rule Based Method in Expert System for Detection Pests and Diseases of Corn
Lilik Sumaryanti, Teddy Istanto, Selfina Pare
Abstract
Abstract Corn is a multi-functional plant, both for direct consumption and as the main raw material for animal feed and the food industry. The need for corn in Indonesia, which continues to increase, needs to be balanced with an increase in production. So that various government policy strategies are carried out, in an effort to increase productivity. Constraints in the cultivation of corn, namely farmers have limitations in identifying diseases that attack plants, and ways to control pests and diseases. The purpose of this study is to propose the use of technology in agriculture by developing an expert system for the detection of corn pests and diseases, which will provide information and strategies for controlling pests and diseases, in order to reduce losses due to crop failure. The knowledge base in expert system contains a set of rules that use the IF-THEN pattern, and to reason on a rule base using forward cahaining method. Expert system is a tool to detection pests and diseases and how to control them like providing expert assistance. In addition, system also provides explanation facility related to the diagnosis results, according to the symptoms obtained from the user. The accuracy detecting pests and diseases 76.6%.