Performance of multi-criteria recommender system using cosine-based similarity for selecting halal tourism

Nadhifah, Rizqi Aulia, Arif, Yunifa Miftachul, Nurhayati, Hani and Angreani, Linda Salma (2022) Performance of multi-criteria recommender system using cosine-based similarity for selecting halal tourism. Applied Information System and Management (AISM), 5 (2). pp. 111-116. ISSN 2621-2544

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Tourism is an activity where people or groups travel voluntarily for relaxation, seeking entertainment, or enjoy cultural diversity both within the city, outside the city, or even abroad. For traveling, information about halal tourism is essential that tourists must know. Tourists can contact a tour guide to find information and recommendations for halal tourism. However, it will cost quite a bit and need for a recommendation system to obtain recommendations and make it easier for tourists to determine which halal tourism to visit. This study aims to obtain the Multi-Criteria Recommender System's (MCRS) performance using cosine-based similarity to select halal tourism in Batu City. MCRS extends the traditional approach by using more than one scoring criteria to generate recommendations. The implementation of MCRS using cosine-based similarity succeeded in producing the five highest recommendations for halal tourist attractions, which were implemented in a game-based system. Through recommendation accuracy testing on two items, three items, four items, and five tourist attractions items, we obtained an average accuracy is 77,95%.

Item Type: Journal Article
Subjects: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080102 Artificial Life
Divisions: Faculty of Technology > Department of Informatics Engineering
Depositing User: Yunifa Miftachul Arif
Date Deposited: 22 Nov 2022 10:31


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