Prediction of the number of daily active COVID-19 in Indonesia

Abstract

In Indonesia, the coronavirus disease (COVID-19) decreased from April to May 2022 and in-creased slowly from May to June 2022. Statistical predictions are needed to monitor the increase in cases of this pandemic spike, as happened at the end of February 2022. This study aims to predict the rise in the number of active COVID-19 cases by applying the autoregressive integrated moving average (ARIMA) mathematical model. and multiple linear regression (MLR). Daily observation data of active cases, new cases, recovered cases, and deaths were recorded from January to June 2022 totalling 152 observations. Then ARIMA modelling for active cases and MLR modelling for daily active case observation data that depended on new cases were carried out , recovered, and died. Furthermore, the prediction results from the two models were determined the root mean squared error (RMSE), the mean absolute error (MAE), and the mean absolute percent error (MAPE). From the calculation results, the ARIMA model is smaller than the MLR. However, the prediction of the next thirty days in the MLR model is close to the actual value, while in the ARI-MA model it is below the actual value.

Keywords

• covid-19
• prediction
• arima
• mlr