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All Journal Jurnal Informatika Ekonomi Bisnis Jurnal Informatika Ekonomi Bisnis
Weni Astika
STIE Bina Karya Tebing Tinggi
Economics, Econometrics & Finance

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The Autoregressive Integrated Moving Average (ARIMA) Model for Predicting Jakarta Composite Index Didik Gunawan; Weni Astika
Jurnal Informatika Ekonomi Bisnis Vol. 4, No. 1 (2022)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (300.144 KB) | DOI: 10.37034/infeb.v4i1.114

Abstract

The 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%.
The Autoregressive Integrated Moving Average (ARIMA) Model for Predicting Jakarta Composite Index Didik Gunawan; Weni Astika
Jurnal Informatika Ekonomi Bisnis Vol. 4, No. 1 (2022)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (300.144 KB) | DOI: 10.37034/infeb.v4i1.114

Abstract

The 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%.
Co-Authors Didik Gunawan