Analisa Implementasi Metode Fuzzy Time Series Jasim pada Prediksi Perkembangan COVID-19 di Indonesia - Dedy Rahman Prehanto; Ginanjar Setyo Permadi; Melvin Nurdiansari (JSINBIS (Jurnal Sistem Informasi Bisnis), 2021)
The pandemic of COVID-19 that has been going on since March 2020 until now has weakened many sectors in many countries an Indonesia as well. In Indonesia, more than 9,000 people have died because of this pandemic. In the first week, 56 cases of COVID-19 were recorded and the cases continued to increase to more than 2,000 cases per week so that the increasing number of cases could result in a lack of service provision and facilities for medical. This study aims to determine the forecasting scheme and how the development of COVID-19 cases that occur in Indonesia. Fuzzy Time Series Jasim method that is applied to find out how to do forecasts by managing previous data.  This method uses the determination of the width of the interval, the formation of a set from historical data and using of the average based length method. In this method also used grouping and data relations that have been fuzzified. From the method that has been used, it can be seen that the results obtained from the Fuzzy Time Series Jasim method are obtained from the accuracy rate of the accuracy error using MAD of 286. And the error magnitude of the forecasting results with the actual data using MAPE is 2.43%. Where it can be concluded that the use of Fuzzy Time Series Jasim method in this study provides good forecasting results