<![CDATA[The rapid growth of tourist destinations in Batu City has posed challenges for travel agencies in designing efficient tourism routes. Ineffective routing can lead to extended travel time, tourist dissatisfaction, and operational inefficiencies. This study aims to design optimal tourism routes using the Minimum Spanning Tree (MST) method through Prim’s algorithm and to compare manual calculations with those generated by QM for Windows software. A descriptive quantitative approach with a replication model was employed, involving one purposively selected key informant—a travel coordinator at Tour and Travel Agency X—due to their expertise in route planning. Primary data were collected through structured interviews, while secondary data, including inter-location distances, were sourced from Google Maps and internal documents. The sample comprises four predefined tour packages. Analysis involved constructing a weighted graph, followed by MST calculations conducted manually and using QM for Windows. Results indicate that QM for Windows consistently produces shorter routes than manual computation. However, practical implementation still requires consideration of real-world factors such as road conditions and agency policies. This study offers practical insights for data-driven tourism route planning and contributes to more efficient and customer-centered travel operations.]]>
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