Modeling and Forecasting of COVID-19 Confirmed Cases in Indonesia Using ARIMA and Exponential Smoothing

DOI

10.2991/aer.k.201221.043How to use a DOI?

Keywords

Forecasting, COVID-19, ARIMA

Abstract

The number of confirmed COVID -19 cases in Indonesia is increasing rapidly. Therefore forecasting of the number of confirmed cases in the future needs to be predicted, so that the government can prepare to handle this pandemic case. The purpose of this study is to provide information on the estimated number of COVID -19 cases in the future in Indonesia. The data used are daily time series data, the number of confirmed cases of COVID-19 from March to August 2020. This study applies two mathematical models, namely: ARIMA and exponential smoothing. Based on ARIMA model, the parameter equations of the ARIMA model (0,2,1), (1,2,0), and (1,2,1) are obtained. The calculation results of Akaike’s Information Criterion (AIC) and Schwartsz Bayesian Criterion (SBC), ARIMA (1,2,1) is the most suitable model. The exponential smoothing model, the model with the smallest root mean square error (RMSE) is obtained namely the exponential smoothing model involving trends. The results of the RMSE calculation of the two models, the ARIMA (1,2,1) model is the most suitable forecast the number of COVID -19 cases in Indonesia.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hedi
AU  - M.V. Joyce Merawati BR
PY  - 2020
DA  - 2020/12/22
TI  - Modeling and Forecasting of COVID-19 Confirmed Cases in Indonesia Using ARIMA and Exponential Smoothing
BT  - Proceedings of the International Seminar of Science and Applied Technology (ISSAT 2020)
PB  - Atlantis Press
SP  - 253
EP  - 258
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.201221.043
DO  - 10.2991/aer.k.201221.043
ID  - 2020
ER  -