Abstract— The Sumba region, Indonesia, is known for its
extraordinary natural beauty and unique cultural richness.
There are 19 interesting tourist attractions spread throughout
the area, but tourists often face difficulties in planning efficient
visiting routes. From this case, it can be solved by applying
graph theory in terms of searching for the shortest distance
which is completed using the shortest path search algorithm.
Then these 19 tourist objects are used to build a weighted graph,
where the nodes represent the tourist objects and the edges of
the graph describe the distance or travel time between these
objects. Therefore, this research aims to compare the shortest
path search algorithm with parameters to compare the shortest
distance results, algorithm complexity and execution time for
tourism in the Sumba area. The results of this research involve
a comparison of several shortest path search algorithms, with
the aim of finding the shortest distance results, algorithm
complexity, and execution time for tourism in the Sumba area.
Based on the test results of the five algorithms with the
parameters that have been prepared, and the findings show that
each algorithm has its own characteristics, the results are as
follows: Dijkstra's algorithm can be used to calculate the
shortest route for single-source and single-destination types.

This resembles the Bellman-Ford algorithm, only the Bellman-
Ford algorithm can be used simultaneously on graphs that have

negative weight values. Meanwhile, the Floyd-Warshall
algorithm is suitable for use on the all-pairs type. Then, the
Johnson Algorithm can be used to determine the shortest path
from all pairs of paths where the destination node is located in
the graph. Finally, the Ant Colony algorithm to compute from a
node to each pair of destination nodes.