Forecasting Method Using the Minitab Program

Abstract

The Corona Virus 2019 (COVID-19) pandemic has yet to subside. This epidemic has spread to almost all countries in the world. This pandemic has resulted in the decrease of the activities of people and the economy. The COVID-19 pandemic itself spread in Indonesia on March 2, 2020, to be precise. Two people tested positive for COVID-19, and they were referred to as case 1 and 2. After the detection of the COVID-19 pandemic in Indonesia, Indonesia experienced additional positive cases of COVID-19 every day. This study aims - to build a model to predict the development of COVID-19 cases based on time series data and the number of COVID-19 sufferers, using seven forecasting methods, namely, Exponential Smoothing, Exponential Smoothing with Trend, Linear Regression/Least Squares, Moving Average, Trend Analysis (Regression Over Time), Additive Decomposition (Seasonal), and Multiplicative Decomposition (Seasonal), with the Minitab program, including in Indonesia. The results showed that the Exponential Smoothing with Trend method, has mean absolute deviation (MAD) of  220.6and mean squared error (MSE) of 69,994.2; the forecast resulted  in 177,621 number of COVID-19 cases, which is predicted to occur on September 1, 2020.