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All Journal Jurnal Pendidikan dan Pembelajaran Jurnal Penelitian Fisika dan Aplikasinya (JPFA) E-SOSPOL Jurnal Kesehatan Masyarakat JREC (Journal of Electrical and Electronics) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer REKAYASA Scientific Journal of Informatics PALAPA: Jurnal Studi Keislaman dan Ilmu Pendidikan Jurnal Ilmu Komputer dan Bisnis The Journal of Society and Media Jurnal Entitas Sosiologi Journal of Vocational Education Studies JTM
Nurul Hidayat
IAIN Tulungagung, Jl. Mayor Sujadi No. 46, Tulungagung
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Journal : Scientific Journal of Informatics

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Halal Food Restaurant Classification Based on Restaurant Review in Indonesian Language Using Machine Learning Hidayat, Nurul; Hakim, M. Faris Al; Jumanto, Jumanto
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.33395

Abstract

Purpose: Halal tourism or muslim friendly tourism has big potential for the tourism industry in Indonesia. According to Cresent Rating, the world’s leading authority on halal-friendly travel, one of the indicators for halal tourism is the availability of choices for halal foods. To support halal tourism, unfortunately, not all restaurants around the tourism object or in the city where the tourism object is located have labels or information that makes people know about halal food in the restaurant easily.Methods/Study design/approach: The data in this research was obtained from online media such as Google Maps, TripAdvisor, and Zoomato. The data consists of 870 data with the classification of halal food restaurants and 590 data with the reverse classification. Machine learning methods were chosen as classifiers. Some of them were Naive Bayes, Support Vector Machine, and K-Nearest Neighbor. Result/Findings: The result from this research shows that the proposed method achieved an accuracy of 95,9% for Support Vector Machine, 93,8% for Multinomial Naive Bayes, and 91% for K-Nearest Neighbor. In the future, our result will be to support the halal tourism environment in terms of technology. Novelty/Originality/Value: In this study, we utilize restaurant reviews done by visitors to get information about the classification of halal food restaurants.
Co-Authors Abdul Hafid Paronda Ahmad Taufiq Al-Hadi, Robith Abdillah aloysius mering Andayani, Trijayanti Putri Andy Usman Aris Tjahyanto Awaris, Ahmad Fauzan Baiq Lily Handayani Candra Dewi Era Budi Prayekti Fery Wongso, Fery Firman Firman Gesit Thabrani Hakim, M. Faris Al Hary Yuswadi Holidi Holidi Imam Cholissodin Indahsari, Amalia Nur Jumanto Unjung Mu’allifin, Isnatul Nadirah, Ulfa Nugroho Adi Pramono, Nugroho Adi Paronda, A. Hafid Raudlatul Jannah Rina Christanti, Rina Ristanti, Kurnia Samsul Hidayat Sanjaya, Beni Bayu Siti Nurhayati Sri Marini Sunaryono Sunaryono, Sunaryono Sutrisno . Usada, Bero Widayanti, Nike Yundari, Yundari