Time series analysis and forecasting of coronavirus disease in Indonesia using ARIMA model and PROPHET

Abstract

The spread of COVID-19 has caused it to be a pandemic. This has caused massive disruption to our daily lives, both directly and indirectly. We aim to utilize Machine Learning model in attempt to forecast the trend of the disease in Indonesia with finding out the approximation when normality will return. This study uses Facebook’s Prophet Forecasting Model and ARIMA Forecasting Model to compare their performance and accuracy on dataset containing the confirmed cases, deaths, and recovered numbers, obtained from the Kaggle website. The forecast models are then compared to the last 2 weeks of the actual data to measure their performance against each other. The result shows that Prophet generally outperforms ARIMA, despite it being further from the actual data the more days it forecasts.