Open AccessTourism Site Recommender System Using Item-Based Collaborative Filtering Approach
Author(s) -
Robertus Adi Nugroho,
Agnes Maria Polina,
Yohanes Dicky Mahendra
Publication year - 2020
Publication title -
international journal of applied sciences and smart technologies
Language(s) - English
Resource type - Journals
eISSN - 2685-9432
pISSN - 2655-8564
DOI - 10.24071/ijasst.v2i2.2987
Subject(s) - recommender system , collaborative filtering , tourism , computer science , filter (signal processing) , consumption (sociology) , information filtering system , information retrieval , data mining , world wide web , geography , computer vision , social science , archaeology , sociology
Many people like traveling. But, often they are difficult to find a tourism site that they like much. Too many information about tourism is the problem. To overcome this problem, we need to filter the information. Recommender System could filter the information. By considering the advantages, the system used item-based collaborative filtering approach to give recommendation. Some tourism site around Yogyakarta province were used in this research. The system is able to give recommendation to users. The accuracy of the rating prediction is 0,6293 and the average time consumption is 1693,33 millisecond.