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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Briliant: Jurnal Riset dan Konseptual Journal of Development Research Applied Information System and Management Jurnal ULTIMATICS
Linda Salma Angreani
Universitas Islam Negeri Maulana Malik Ibrahim
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences

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Journal : Applied Information System and Management

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Performance of Multi-Criteria Recommender System Using Cosine-Based Similarity for Selecting Halal Tourism Rizqi Aulia Nadhifah; Yunifa Miftachul Arif; Hani Nurhayati; Linda Salma Angreani
Applied Information System and Management (AISM) Vol 5, No 2 (2022): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v5i2.25035

Abstract

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%.
Performance of Multi-Criteria Recommender System Using Cosine-Based Similarity for Selecting Halal Tourism Nadhifah, Rizqi Aulia; Arif, Yunifa Miftachul; Nurhayati, Hani; Angreani, Linda Salma
Applied Information System and Management (AISM) Vol. 5 No. 2 (2022): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v5i2.25035

Abstract

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%.
Co-Authors Abd. Charis Fauzan Hani Nurhayati Jimmy Bunardi, Jimmy Muhammad Faisal Nadhifah, Rizqi Aulia Novrindah Alvi Hasanah Randy Agustian Kusuma, Randy Agustian Rizqi Aulia Nadhifah Shofiyatun Najah Shofiyatun Najah Tamaulina Br Sembiring Yunifa Miftachul Arif