Implementation of A* and Dijkstra Algorithms for Optimal Pathfinding: A Case Study of Nearest Hospital Location from Bina Nusantara University

In this study, we implement and evaluate A* and Dijkstra’ s pathfinding algorithms to find the nearest hospital from Bina N usantara University (BINUS) in Jakarta, Indonesia. To address the urgent need for efficient routing in emergency situations, we first collect location data using Google Maps and model it in a graph structure. Both algorithms are then applied to determine the shortest path from the university to nearby hospitals. Dijkstra's algorithm consistently produces optimal paths, but its computational complexity increases with the number of nodes and edges, making it less efficient in densely connected urban areas. In contrast, the A* algorithm leverages heuristic estimates to prioritize nodes, reducing processing time and proving more effective for large-scale, dynamic navigation scenarios. Our evaluation shows that A* is more suitable for real-time pathfinding in cities, while Dijkstra's algorithm is better suited for smaller or less complex networks. Future work could improve algorithm efficiency by incorporating real-time traffic data, developing advanced heuristics, exploring hybrid methods, and investigating alternative algorithms for urban navigation challenges.