TRAVELING SALESMAN PROBLEM INTEGRATED WITH FUZZY LOGIC ON TOURISM IN D.I. YOGYAKARTA

The optimization of tourist travel routes has become a crucial factor in enhancing travel efficiency, reducing costs, and optimizing the overall tourist experience. This study focuses on the innovative integration of fuzzy logic with the Traveling Salesman Problem (TSP) to determine the optimal path for visiting several major tourist destinations in the Special Region of Yogyakarta, a methodological approach not previously explored in existing literature. Initially, we perform data fuzzification, followed by fuzzy inference, to obtain fuzzy outputs. These output values are subsequently used to determine the shortest route using TSP. Several algorithms are utilized, including Minimum Spanning Tree (MST) and Nearest Neighbor (NN). The results show that the Prim algorithm in MST generates the most optimal route, with a travel distance of 223.1 km and a travel time of 442 minutes. Integrating fuzzy logic into the TSP framework effectively addresses uncertainties in distance and time, offering a solid foundation for improved travel route planning.