AN EXPERT SYSTEM USING FUZZY-DEMPSTER SHAFER FOR IDENTIFICATION OF PEST AND DISEASE OF CORN PLANT

Abstract

Dempster Shafer is a widely used method in reasoning expert system. Conclusion to a problem in the method based on combining two evidence (facts) that exist, which each have a measure of confidence that stated in the density m1 and m2.

This study will determine the density values ​​(m) using fuzzy logic. Fuzzy input is the rate of onset of symptoms and level of uniqueness of symptoms, while the fuzzy output is crisp values ​​of the probability density. The degree of certainty of an expert answer given by symptoms then calculated using Dempster combination rule. Implementation of this research is an expert system for the identification of pests and plant diseases corn. Applications is able to take advantage of the expert system in order to provide knowledge and expertise on pest eradication method.

Expert systems are designed to give results based on the identification of symptoms entered. Determining the type of pest or disease that attacks based on the process of finding a confidence value to a diagnosis. The greater the value of the trust, the greater the potential for pests / diseases that attack, and vice versa.