Forecasting of the Cases of Covid-19 Patients in Indonesia using Fuzzy Time Series

Abstract

The main objective of this study is forecasting of the cases of covid-19 patients in indonesia using fuzzy time series. The data used is from February 1, 2022 to February 28, 2022. The methods used are Fuzzy Time Series (FTS) Chen and FTS Cheng, using first order and second order. FTS is a forecasting method that uses rules and logic on fuzzy sets. The level of prediction accuracy is then calculated based on the Mean Absolute Percentage Error (MAPE) value. The MAPE values of these two methods are then compared to know which method is more suitable in this case study. The results showed that Fisrt Order FTS Chen produced an accuracy of 4,21% and Fisrt Order FTS Cheng produced an accuracy of 4,22%. Second Order FTS Chen and Second Order FTS Chen produced/1the same MAPE, 1,23%./1The results of this study indicate that Second Order FTS Chen and FTS Cheng produce good accuracy and can be used to predict new confirmed cases of Covid 19 sufferers in Indonesia.