Macroeconomic Factor Analysis of Composite Stock Price Index (IHSG) Returns Period (2020-2025) Using Multiple Linear Regression - Roy Andreas Sibarani; Steven Sembiring; Mika Riawaty Sibarani; Zepandi Ramadhan (Journal of Intelligent Computing and Advanced Data Science, 2026)
The Jakarta Composite Index (JCI) is the main indicator used to describe the performance of the Indonesian capital market. JCI movements are influenced by various macroeconomic factors that can influence investment decisions and financial market stability. This study aims to analyze the influence of macroeconomic factors consisting of the USD/IDR exchange rate, the BI Rate, gold prices, and inflation on JCI returns for the 2020–2025 period. The data used are monthly data obtained from Yahoo Finance, Bank Indonesia, and the Central Bureau of Statistics. The research method used is Python-based multiple linear regression with analysis stages including return transformation, stationarity test using Augmented Dickey-Fuller (ADF), multicollinearity test using Variance Inflation Factor (VIF), and classical assumption testing using Durbin-Watson, Breusch-Pagan, and Jarque-Bera. The results show that changes in the USD/IDR exchange rate have a negative and significant effect on JCI returns. Conversely, changes in the BI Rate, gold prices, and inflation do not show a significant effect at the 5% significance level. The developed model explains 43.6% of the variation in JCI returns and meets the required statistical assumptions. These findings demonstrate that the exchange rate is the most dominant macroeconomic factor influencing JCI returns during the study period. These results are expected to serve as a reference for investors and researchers in understanding the relationship between macroeconomic conditions and the Indonesian capital market.