<![CDATA[ This study aims to analyze the movement of Islamic stock prices in Indonesia using the shares of Bank Syariah Indonesia (BRIS) as a case study. The research employs the Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) methods to model stock price movements and volatility. Daily historical stock price data from January 1, 2020, to July 30, 2025, were collected and analyzed through several stages, including stationarity testing, selection of the best ARIMA model, and heteroskedasticity testing to determine the most appropriate GARCH model. The results indicate that the ARIMA (1,1,0) and GARCH (2,2) models provide the best performance for forecasting the stock price movements of Bank Syariah Indonesia. The forecasting results show a relatively high level of predictive performance, with prediction accuracy ranging from 90.2% to 98.3%. The analysis also reports a maximum Mean Absolute Percentage Error (MAPE) value of 111%, indicating that forecasting errors may vary across the observation period. The findings are expected to provide useful information for investors and other market participants in supporting investment decision-making related to Bank Syariah Indonesia's shares.]]>
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