<![CDATA[The Indonesia Emas 2024 Vision emphasizes the importance of educational development in improving future human resources, particularly for the productive-age population in 2045. Enhancing access and participation through equitable education distribution and removing geographic barriers has become a primary focus in achieving educational targets. This study aims to explore the potential of utilizing Dijkstra’s algorithm for granular mapping of school distances from residential areas. The analysis involved calculating school distances on a 1 km populated grid in West Nusa Tenggara, using 2019 infrastructure data, residential tagging, and road graphs from OpenStreetMap. The results demonstrate the potential of the Dijkstra algorithm in granular mapping of school distances and reveal that 21.84% of the population in the area must travel more than 5 km to access senior high school education, and 8.11% for junior high school. This study also discusses the limitations and drawbacks of this approach and explores potential improvements for identifying areas that face challenges in accessing educational facilities.]]>
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