Open AccessApplication of Fuzzy Quality on Dempster-shafer for Pest and Disease Diagnosing of Chili (Case Study on Tidal Swamp Land)
Author(s) -
Muliadi Muliadi,
Irwan Budiman,
Antar Sofyan,
Muhammad Adhitya Pratama,
Nurdin Nurdin
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/536/1/012125
Subject(s) - dempster–shafer theory , expert system , fuzzy logic , artificial intelligence , computer science , swamp , data mining , machine learning , ecology , biology
Expert systems are usually used only to help get the results of a diagnosis faster. In the expert system, a method usually used to support a diagnosis process. In this research using the method of Fuzzy and Dempster-Shafer. Fuzzy methods used to find the scale of values belief a fact with fuzzyfication process, while the Dempster-Shafer method used to combine pieces of the facts to calculate the likelihood of an event. The purpose of this study was to determine whether the method of Fuzzy and Dempster-Shafer can be applied to the expert system to provide disease diagnosis chili. Where the results of the expert system will produce a presentation about the likelihood of diagnosis of plant diseases chili. Fuzzy weights obtained are Low 0.15, Medium 0.4 and High 0.65.