<![CDATA[This study investigates the integration of Decision Tree analytics and SWOT analysis in enhancing service quality and information security in Islamic banking. Using a cross-sectional explanatory design, the research combines transaction-level customer data modeled through a Decision Tree classifier with survey data from 270 customers of Bank Syariah Indonesia. The Decision Tree model demonstrates strong classification performance, with satisfactory accuracy, sensitivity, and specificity in identifying customer risk profiles. Multiple regression analysis indicates that both Decision Tree utilization and SWOT implementation have positive and statistically significant effects on perceived service quality and security. The Decision Tree shows a stronger direct impact, while SWOT contributes strategically by translating predictive insights into structured planning actions. The findings highlight the complementary relationship between predictive analytics and strategic management. This study contributes to the literature by bridging machine learning applications and strategic frameworks in Islamic banking and provides managerial implications for data-driven governance and service optimization.]]>
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