Open AccessDevelopment of a Land Transportation Recommendation System Using the Hill Climbing Algorithm
Author(s) -
Eka Surya Aditya,
Wikan Danar Sunindyo
Publication year - 2020
Publication title -
international journal of engineering and applied science research
Language(s) - English
Resource type - Journals
ISSN - 2745-6455
DOI - 10.26418/ijeasr.v1i1.41312
Subject(s) - climbing , public transport , computer science , hill climbing , recommender system , mode (computer interface) , quality (philosophy) , space (punctuation) , algorithm , transport engineering , land use , machine learning , engineering , civil engineering , philosophy , structural engineering , epistemology , operating system
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.