| dc.description.abstract | The significant economic growth and population increase in the city of Medan have
led to a rise in mobility demand, thereby triggering traffic congestion issues. A solution
to this problem lies in the development of a Light Rail Transit (LRT) system. In this
process, determining potential locations for LRT stations is crucial. The selected
locations must satisfy four key aspects: environmental, economic, accessibility, and
operational aspects. From the identified potential locations, two route
recommendations for LRT development were provided, using the shortest path
algorithm. This study focuses on the comparison between Dijkstra's algorithm and the
A* algorithm, measured based on each algorithm's complexity, the number of station
points, the total distance of the route produced by each algorithm, and the time
required by each algorithm to find the shortest path. Both algorithms employ a greedy
approach, selecting the path deemed shortest at each step. Dijkstra's algorithm finds
the shortest path by exploring all possible pairs of points, while A* finds the shortest
path using a heuristic value. This study found that for the first route recommendation,
Dijkstra's algorithm and the A* algorithm yielded the same shortest path, with the
same number of points and total distance. However, for the second route
recommendation, Dijkstra's algorithm found a shorter total distance compared to the
distance produced by the A* algorithm. In terms of time, the A* algorithm was faster
than Dijkstra's algorithm. This research provides a reference for determining the
shortest path and selecting optimal LRT station locations | en_US |
