<![CDATA[Public transport is essential for sustainable urban mobility, but challenges such as limited capacity, operational inefficiency, and service performance remain. This study develops a Decision Support System (DSS) that integrates operational data, passenger preferences, and performance indicators to provide recommendations for decision-making. The study uses passenger surveys, system performance analysis, and data analysis and prediction techniques. The DSS incorporates information visualization, performance monitoring, and scenario analysis to help decision-makers anticipate potential outcomes and make informed choices. The results demonstrate improvements in service performance, with passenger satisfaction increasing from 76% to 95%, while prediction accuracy exceeded 90%. These findings indicate that the DSS can support more effective decision-making and resource allocation while improving transparency and accountability in public transport services. The system also aligns with efforts to promote technology-driven urban development. Overall, integrating data and decision-support technologies can improve public transport operations, support better resource utilization, and contribute to more sustainable and inclusive urban mobility.]]>
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