FORECASTING OF COVID-19 DAILY CASES IN INDONESIA USING ARIMA MODEL - Zia Azuro Zuhairoh; Yuliana Sarasati (Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population), 2022)
COVID-19 (Coronavirus Disease 2019) continues to be a global issue. The disease began to spread due to direct contact with the seafood market in Wuhan, Hubei Province, China. COVID-19 cases globally and especially in Indonesia, are still increasing as well. Therefore, it is important to forecast future cases as a form of vigilance and materials to formulate strategies in controlling the spread and procurement of health systems. This study aims to predict daily cases of COVID-19 in Indonesia. This research includes non-reactive studies by collecting daily case data on COVID-19 from October 1st to December 31st, 2020 from the COVID-19 Task Force website in Indonesia. The results showed that the model that is fit to describe COVID-19 cases in Indonesia is ARIMA [5,1,0] with a model significance of 0.000 and constant of 0.049 (p value <0.05), Ljung-Box Q of 0.880 (p value >0.05) and residual normality of 0.330 (p value >0.05). The three months forecasting (from January to March 2021) showed a number that tended to increase. The increase in cases occurred due to environment, behavior, health services, and genetics. Therefore, it is necessary to increase cooperation between the government and the community so that efforts to suppress the growth of COVID-19 cases are optimal.