<![CDATA[Forest and land fires are critical emergencies requiring rapid response to minimize casualties and property damage. In urban areas like Praya City, fire department response delays are often caused by inefficient routing, especially with traffic congestion and complex road infrastructure. This study aims to analyze and compare the performance of Dijkstra's and Bellman-Ford's algorithms for optimizing firefighter routes in Praya City. This quantitative research utilized a computational and comparative analysis approach. Road network data from Praya City was obtained from Google Maps and modeled as a static graph consisting of 17 nodes and weighted edges repre-senting actual distances. Dijkstra's and Bellman-Ford's algorithms were implemented in Python to find the shortest routes from a designated starting point (Fire Department office) to all other nodes. Performance was evaluated based on route optimality, completeness, and computation time. Both Dijkstra's and Bellman-Ford's algorithms successfully identified identical optimal shortest routes for all tested origin-destination pairs within the Praya City graph. However, Dijkstra's algorithm demonstrated significantly superior computational efficiency, with an average computation time of 0.5 seconds, compared to Bellman-Ford's 1.5 seconds. For optimizing firefighter routes on the static road network graph of Praya City, Dijkstra's algorithm is recommended due to its combi-nation of optimality and superior speed. This finding provides an empirical basis for developing more efficient emergency response navigation systems. Future research should focus on inte-grating dynamic parameters like real-time traffic data.]]>
