<![CDATA[Stock prices often experience unpredictable changes, leading to the uncertainty of stock return values. This paper aims to find a mathematical model to predict future stock prices based on past stock price data. One of the models used to predict stock prices is the Brownian Motion Model, which is based on the concept of random movement. The research method used to solve the stock forecasting problem is by using Geometric Brownian Motion by calculating the return value of closing stock prices using Ms. Excel, testing the normality of return value data, modeling stock prices using Geometric Brownian Motion, and calculating the model’s accuracy level using MAPE. Based on the model, the accuracy level using MAPE from the calculation results is obtained with a MAPE value of less than 10%, which is 4,93%. Therefore, it can be concluded that the average error deviation generated indicates a high level of forecasting accuracy.]]>
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