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All Journal Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population)
Zia Azuro Zuhairoh
Faculty of Public Health, Universitas Airlangga, 60115 Surabaya, East Java, Indonesia

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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) Vol. 11 No. 1 (2022): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v11i1.2022.28-35

Abstract

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.
Co-Authors Yuliana Sarasati