Abstract
Communities in big cities often encounter problems in using public transportation due to difficulties in accessing available information. The information is not well integrated and scattered in various places. For this reason, an information and recommendation system is needed to facilitate the public in choosing the right mode of land transportation. The recommendation system can be built using the Hill Climbing algorithm. In this paper, I explain the development of a public land transportation recommendation system using three types of Hill Climbing Algorithms. The results of the recommendations are analyzed based on the complexity of asymptotic time, space complexity, and the quality of the results.
Published Version
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