Design and Development of Fuzzy Logic Application Tsukamoto Method in Predicting the Number of Covid-19 Positive Cases in West Java | Zendy

Alwi Dahlan Permana | Zendy

Open Access

Design 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 , fuzzy inference system , artificial intelligence , computer science , java , fuzzy set , mathematics , fuzzy number , adaptive neuro fuzzy inference system , fuzzy control 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.

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