The Autoregressive Integrated Moving Average (ARIMA) Model for Predicting Jakarta Composite Index
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Keywords:
Autoregressive Integrated Moving Average (ARIMA), Index, Jakarta Composite, Forecasting, Covid-19
AbstractThe purpose of this study is to test the ability of the Autoregressive Integrated Moving Average (ARIMA) model to predict the value of the Jakarta Composite Index (JKSE) which fluctuates greatly due to the Covid-19 pandemic. The population in this study is JKSE daily closing price data for the period January 2020 to April 2021, so the sample in this study is 324 time series data. The results showed that the best ARIMA model for predicting the value of the Jakarta Composite Index was ARIMA (3,1,9). ARIMA (3,1,9) can predict the JKSE value very well because the value of the forecasting results is not much different from the actual value. This is also evidenced by the results of the accuracy test using MAPE which has a result of 1,729 which means the accuracy of forecasting is 98,27%. Downloads
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Published
2022-02-21
Section
Articles
How to Cite
Gunawan, D., & Astika, W. (2022). The Autoregressive Integrated Moving Average (ARIMA) Model for Predicting Jakarta Composite Index. Jurnal Informatika Ekonomi Bisnis, 4(1), 1-6. https://doi.org/10.37034/infeb.v4i1.114
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