Peramalan Kasus Covid-19 Di Kota Palu Menggunakan Metode Forecasting Model Autoregressive Integrated Moving Average (ARIMA)

PUTRI AMELISA. Forecasting COVID-19 Cases in Palu City through Forecasting Model of Autoregressive Integrated Moving Average (ARIMA) (under the supervisions of Nurhaya S. Patui)

Biostatistics, Family Planning and Population Department
Public Health Study Program
Public Health Faculty
Tadulako University, Palu

SARS-CoV-2, also known as COVID-19, is an infectious disease with acute respiratory disorders that causes complications such as acute respiratory failure and pneumonia, which can cause death for sufferers. Forecasting the number of COVID cases so that the government can plan prevention to minimize transmission. The purpose of this study is to find out the best ARIMA model that can be used to predict the number of positive cases of COVID-19 in Palu City. The method applied in this study was descriptive quantitative using time series forecasting techniques through the ARIMA model. The data used was secondary data on the number of positive cases of COVID-19 in Palu City for the 2020–2022 period. This study aims to find the best ARIMA model that can be used to predict the number of positive cases of COVID-19 in Palu City. The method used in this study is descriptive quantitative using time series forecasting techniques using the ARIMA model. The data used is secondary data on the number of positive cases of COVID-19 in Palu City for the 2020–2022 period. The results of this study indicate that the forecast for the number of positive cases of COVID-19 in Palu City is 4.14 in October 2022, it is 7.25 in November, it is 14.76 in December, it is 23.30 in January 2023, it is 34.18 in February, and it is 49.08 in March with a MAPE of 0.39 and the conclusion that the model is very good for forecasting because the MAPE value is <10.Â

Keywords: COVID-19, Time Series, Forecasting, ARIMA