Open AccessDesign and Development of Fuzzy Logic Application Tsukamoto Method in Predicting the Number of Covid-19 Positive Cases in West Java
Author(s) -
Alwi Dahlan Permana
Publication year - 2020
Publication title -
international journal of global operations research
Language(s) - English
Resource type - Journals
eISSN - 2723-1747
pISSN - 2722-1016
DOI - 10.47194/ijgor.v1i2.35
Subject(s) - fuzzy logic , covid-19 , defuzzification , artificial intelligence , java , fuzzy inference system , computer science , fuzzy set , fuzzy rule , mathematics , psychology , fuzzy number , fuzzy control system , adaptive neuro fuzzy inference system , medicine , programming language , disease , infectious disease (medical specialty)
The increase in covid-19 positive patients in Indonesia, especially in West Java, is unpredictable, resulting in unpreparedness in dealing with covid-19 cases. People in monitoring and patients under supervision are the category that is breast-positive patients after passing the incubation period for 14 days. Fuzzy logic is one derivative of artificial intelligence that is able to predict a thing.The study used the fuzzy logic of the Tsukamoto method to predict the percentage increase in positive cases of covid-19 with measures performed are fuzzification, rule formation, inference, and defuzzification. The results showed a 4.5% error rate indicating that predicting covid-19 using the fuzzy logic of the Tsukamoto method was successful.