Destinations Ratings Based Multi-Criteria Recommender System for Indonesian Halal Tourism Game

Abstract

Halal tourism is one of the tourism products that have the prospect of contributing to economic growth in Indonesia. Therefore, the government needs to increase promotions to increase tourist interest in halal tourism destinations in Indonesia. Game is one of the alternative promotional media that can also function as an educational medium for choosing halal tourism that is fun for potential tourists. This study proposes a recommendation system to support knowledge sources in the Indonesian halal tourism game. We use destinations ratings-based multi-criteria recommender system (MCRS) to generate recommendation rankings as a reference for visualizing halal travel for players as potential tourists. This method improves the ability of the conventional tourism recommendation system, which is generally based on a single criterion. In this study, we use eight destinations rating criteria as a reference for calculating the recommender system in the halal tourism game. Each of these criteria is a reference for tourists' assessment of halal tourist destinations in Indonesia. Next, we integrate the cosine-based similarity technique in MCRS to measure the level of similarity between players and previous tourist data sets. This research's testing phase uses the theme of halal tourism destinations in the Batu City area. The test results show that the number and composition of the tourism destinations item rating as input of the recommender system affect the accuracy, precision, recall, and F1 scores. Based on 40 experiments with different tourism destination item rating input configurations, it shows that the average value of accuracy = 0.60, precision = 0.67, recall = 0.64 and F1 score = 0.65.

Selecting Tourism Site Using 6 As Tourism Destinations Framework Based Multi-Criteria Recommender System

“…Each paper also discusses recommender systems in various applications. In comparison, this study produces a higher level of accuracy than paper [8] which is 0.666.…”

“…They implemented the research on halal tourism games so that they used the criteria for halal tourism as a reference for determining the rating. The experimental results in the study show that the average accuracy value of the recommendations is 0.6 [8].…”

“…Table 6 compares this study and several studies on previous recommendation systems taken from the method, application, and accurate results. Where paper [6] uses the Neural Network-Based MCRS method, paper [7] uses the Blockchain and 6AsTD Framework, paper [8] uses the Rating Destinations Based MCRS, while our research uses 6AsTD Based MCRS. Each paper also discusses recommender systems in various applications.…”

Learning Material Selection for Metaverse-Based Mathematics Pedagogy Media Using Multi-Criteria Recommender System

“…In this study, we tried to use the cosine-based similarity technique because it has a more accurate ability to produce recommendations based on multicriteria [13]. Eq.…”

“…Furthermore, the system uses these recommendations as a reference in determining the scenario of the subject matter for them. MCRS is a method of generating recommendations based on multi-criteria that can produce more accurate recommendations than conventional methods based on single criteria [13,14]. In this study, MCRS is responsible for producing recommendations for the choice of subject matter based on the value of several criteria describing the student's understanding level.…”