Forecasting Weekly Stock Price of Jakarta Stock Exchange Composite Index (IHSG) Using ARIMA Box-Jenkins Method

Geovani F Simanjuntak

Abstract


Stock price movements in the capital market reflect investor sentiment and economic trends, requiring accurate forecasting methods to support decision-making. One method that can be used for forecasting is the Autoregressive Integrated Moving Average (ARIMA). The application of the ARIMA method to the weekly stock price data of the Jakarta Stock Exchange Composite Index (IHSG) from November 2023 to April 2025 produces the equation Y, 0.874-1-0.5359+0.66193 + 0.041661-1+0.9721e2+ 0.1892-3+ et which is obtained from ARIMA(2,1,3) as the best model based on the lowest error values (MAE, MSE, RMSE, and MAPE). This model passed residual diagnostics and demonstrates strong potential in forecasting IHSG stock prices.

Keywords


ARIMA; Jakarta Stock Exchange Composite Index; IHSG: Forecasting

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References


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