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Galih Aulia Rahmadanu
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Implementasi Naive Bayes dan Weighted Product Dalam Memberi Rekomendasi Hotel Terbaik Saat Berwisata Di Bali Galih Aulia Rahmadanu; Edy Santoso; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Bali is one of the best tourist destinations in Indonesia. The number of tourists coming to Bali always increases by 300.00 to 500,000 people every year. In 2017 amounting to 62.89% of tourists visiting Bali chose to stay at the hotel. But based on the wrong comments found in one of the largest hotel booking applications in Indonesia, Traveloka is still found to have complaints about hotels that are not in accordance with tourist expectations. Therefore, the hotel recommendation system is made by calculating the value for each of the points considered important in the assessment of a hotel. In this system two methods are used, namely Naive Bayes and Weighted Product. The Naive Bayes method is used to classify the input given by the user into the existing hotel category and the Weighted Product method is used to provide hotel recommendations by doing hotel ranking that is closest to the criteria that the user wants. In this system there are 7 rating points for hotels and hotels divided into 3 categories. The results of system accuracy testing using 50 hotel data resulted in the best level of accuracy of 100%.
Co-Authors Edy Santoso Sutrisno Sutrisno