This research aims to determine predictions of the level of sales of Bank BCA shares by utilizing artificial intelligence technology. By utilizing Big Data Analytics technology to manage and read large amounts of data. This research uses a descriptive qualitative method by applying the Extreme Gradient Boosting (XGBoost) algorithm regression model. The implementation of this machine learning model can be done iteratively and incrementally. while the type of data used is secondary data obtained from the dataset collection site, namely Kaggle. The results of this research create a solution to help companies see predictions of stock profits or losses more easily and this research can also become public information for potential investors who want to buy shares. This research concludes that the use of appropriate machine learning models can show quite good prediction accuracy and become an innovative solution to increase operational efficiency.
                        
                        
                        
                        
                            
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