Efficient route planning plays a crucial role in supporting tourism development, particularly in regions with numerous scattered attractions such as West Java, Indonesia. This study addresses the Traveling Salesman Problem (TSP) by comparing two algorithmic approaches: the Cheapest Insertion Heuristic (CIH) and the Christofides algorithm, to determine the shortest tour among 20 selected tourist sites. Using travel time data obtained from Google Maps, both algorithms were implemented manually and using Python language programming. The manual application of the CIH algorithm resulted in a total travel time of 813 minutes, which was later optimized to 764 minutes after adjustments to eliminate intersecting paths. Meanwhile, the CIH algorithm implemented in Python provided a final route of 717 minutes. In contrast, the Christofides algorithm yielded consistent results for both manual and Python-based calculations, producing a tour with a total travel time of 746 minutes. The findings suggest that the CIH algorithm using Python language offers the most efficient route in this case study. This research contributes to the development of intelligent tour planning systems and can be a valuable reference for optimizing regional tourism logistics.
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