<![CDATA[Customer behavior analysis is crucial for companies, especially Small and Medium Enterprises (SMEs), to make strategic decisions. Through customer behavior analysis, patterns of customer behavior in purchasing a product or service can be identified. This provides insights into preferences and the right strategies to maintain or increase customer loyalty. This research aims to analyze customer behavior using the ensemble logistic regression method. Data was collected from the company's customer database over the last 5 years. Customer behavior is characterized by gender, age, and the preferred vehicle transmission type. The ensemble logistic regression method was implemented to improve model accuracy. The results show that the ensemble technique can enhance the accuracy of the Logistic Regression method. Model accuracy significantly increased with boosting, achieving an accuracy of 76%, while the model with bagging achieved an accuracy of 75%.]]>
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