FORECASTING OF COVID–19 WITH AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) METHOD IN EAST JAVA PROVINCE

Abstract

Background: The COVID-19 pandemic has had a major impact on the world's health system, including Indonesia. The national health system is facing challenges with increasing cases of COVID-19. With the forecasting of COVID-19 cases, it is hoped that it can be one of the references in dealing with COVID-19 and one form of mitigation in dealing with COVID-19. Purpose: This research aims to predict COVID-19 cases in East Java Province for the coming year using the Autoregressive Integrated Moving Average (ARIMA) method based on patient data from March 2020 to January 2022. Methods: This type of research is analytic. Forecasting future COVID-19 cases using the Autoregressive Integrated Moving Average (ARIMA) method based on COVID-19 data from March 2020 to January 2022. Results: Based on the results of ARIMA analysis, the best forecasting model for confirmed cases of COVID-19 is the model (1:0:1) with AIC values ​​(14.22672), SIC (14.33357), while for cured cases is the model (1:2: 3) with the value of AIC (13.93054), SIC (13.03738), and for the case of death is the model (1:2:1) with the value of AIC (10.76105) and SIC (10.86790). Conclusion: From the results of this study, it is predicted that there will be an increase in COVID-19 cases in July 2022, January 2023 and June 2023.