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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Vani Maharani Nasution
Universitas Informatika dan Bisnis Indonesia, Bandung
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Journal : JURNAL MEDIA INFORMATIKA BUDIDARMA

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Perancangan Aplikasi Fuzzy Logic Untuk Prediksi Kasus Positif Covid-19 Menggunakan Metode Tsukamoto Vani Maharani Nasution; Graha Prakarsa
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3338

Abstract

COVID-19 is a virus that attacks the respiratory system which was first discovered in the Chinese city of Wuhan. This virus spreads very quickly and spreads throughout the world, including Indonesia. West Java is the province with the most positive cases of COVID-19, on May 4, 2020, 193 positive cases were added, and on 28 June 2020 there were 1,396 confirmed cases with an additional 18 patients. The unpredictable increase in positive cases of COVID-19 has led to the unpreparedness of officers in handling this outbreak. The West Java Provincial Health Office acknowledged the lack of Covid-19 handling facilities in 52 regional general hospitals in West Java Province to monitor positive COVID-19 patients, one of which was the lack of isolation rooms. In addition, the quality of the isolation room and personal protective equipment does not meet the standards. Predicting an increase or decrease in cases of positive COVID-19 patients needs to be done, so that there is readiness from the task force team for COVID-19 to deal with the problem of lack of facilities including isolation rooms and personal protective equipment. Fuzzy logic is one of the derivatives of artificial intelligence that is able to predict something. The research was conducted using the fuzzy logic of the Tsukamoto method through several stages including fuzzification, formation of rules, inference, and defuzzification. The results showed an error rate of 4.5% which indicated that predicting covid-19 using the fuzzy logic of the Tsukamoto method showed a high success rate
Penerapan Logika Fuzzy Menggunakan Metode Mamdani Pada Prediksi Jumlah Kasus Positif Covid-19 Graha Prakarsa; Vani Maharani Nasution
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3282

Abstract

The Covid-19 pandemic has caused many hospitals around the world to experience difficulties both in terms of management and infrastructure advice in providing services because the number of patients soared in a short time so that treatments such as providing services, facilities, and medical personnel were unpredictable. Therefore, we need an application that can predict the number of positive Covid-19 cases 14 days later to help the Covid-19 Handling Acceleration Task Force team in order to provide the right policies for handling the provision of services, facilities, and medical personnel. Fuzzy logic that can be used to analyze Covid-19 problems that contain uncertainty at this time. The research conducted to design the system was obtained from the observation of existing data, in this study using descriptive research methods. The results of this study conclude that the fuzzy logic of the Mamdani method in predicting the number of positive cases of COVID-19 in West Java Province has an error rate of 50.16%. The application of fuzzy logic in predicting the number of positive cases of covid-19 uses the fuzzy logic model of the mamdani method to predict the number of positive cases of covid-19 in West Java Province with an error rate of 50.16%
Co-Authors Graha Prakarsa