{"title":"基于内容过滤方法的酒店推荐系统(以Nusatrip网站上日惹酒店为例)","authors":"Cheryl Ayu Melyani","doi":"10.36456/jstat.vol15.no1.a5375","DOIUrl":null,"url":null,"abstract":"The increasing of Covid-19 pandemic has hampered people's activities, often causing stress if they are only stay at home continuously. This has led to an increasing trend of staycations or holiday activities in the city itself by renting a hotel. Hotel rental technology has begun to be transferred with the existence of OTA (Online Travel Agent). The existence of various kinds of hotels with various kinds of facilities that makes people feel confused in choosing which hotel to occupy. To help overcome this, the researchers tried to create a recommendation system to help prospective hotel residents choose the hotel according to their choice. In addition, it can also assist companies in increasing hotel room reservations through its website. In this study, researchers will build a hotel recommendation system in Yogyakarta at one of the OTAs in Indonesia using Content-Based Filtering Methods, weighting text data using Term Frequency-Inverse Document Frequency (TF-IDF) Methods and measuring document similarity using Cosine Similarity Methods. Based on the results of the Good Karma Yogyakarta hotel recommendations as a test example, 10 similar hotels were obtained, namely Happy Buddha Yogyakarta – Hostel, Nextdoor Homestay, Hotel Puspita, OYO 426 Hotel Gading Resto, Omah Jegog Homestay, Prawirotaman Homestay, RedDoorz near Prawirotaman, Ayodhya Garden Hostel Yogyakarta by HOM, Bringin House Yogyakarta, and House 24 Yogyakarta with cosine similarity values 0.956666513, 0.946570717, 0.917459394, 0.912534877, 0.886439718, 0.88221982, 0.881775275, 0.875845794, 0.872030219, and 0.871514859.","PeriodicalId":118320,"journal":{"name":"J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hotel Recommendation System with Content-Based Filtering Approach (Case Study: Hotel in Yogyakarta on Nusatrip Website)\",\"authors\":\"Cheryl Ayu Melyani\",\"doi\":\"10.36456/jstat.vol15.no1.a5375\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasing of Covid-19 pandemic has hampered people's activities, often causing stress if they are only stay at home continuously. This has led to an increasing trend of staycations or holiday activities in the city itself by renting a hotel. Hotel rental technology has begun to be transferred with the existence of OTA (Online Travel Agent). The existence of various kinds of hotels with various kinds of facilities that makes people feel confused in choosing which hotel to occupy. To help overcome this, the researchers tried to create a recommendation system to help prospective hotel residents choose the hotel according to their choice. In addition, it can also assist companies in increasing hotel room reservations through its website. In this study, researchers will build a hotel recommendation system in Yogyakarta at one of the OTAs in Indonesia using Content-Based Filtering Methods, weighting text data using Term Frequency-Inverse Document Frequency (TF-IDF) Methods and measuring document similarity using Cosine Similarity Methods. Based on the results of the Good Karma Yogyakarta hotel recommendations as a test example, 10 similar hotels were obtained, namely Happy Buddha Yogyakarta – Hostel, Nextdoor Homestay, Hotel Puspita, OYO 426 Hotel Gading Resto, Omah Jegog Homestay, Prawirotaman Homestay, RedDoorz near Prawirotaman, Ayodhya Garden Hostel Yogyakarta by HOM, Bringin House Yogyakarta, and House 24 Yogyakarta with cosine similarity values 0.956666513, 0.946570717, 0.917459394, 0.912534877, 0.886439718, 0.88221982, 0.881775275, 0.875845794, 0.872030219, and 0.871514859.\",\"PeriodicalId\":118320,\"journal\":{\"name\":\"J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36456/jstat.vol15.no1.a5375\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36456/jstat.vol15.no1.a5375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
Covid-19大流行的加剧阻碍了人们的活动,如果他们只是连续呆在家里,往往会造成压力。这导致了一个越来越多的趋势,即通过租酒店在城市本身的住宿或度假活动。随着OTA (Online Travel Agent)的出现,酒店租赁技术已经开始转移。各种酒店的存在,各种设施,使人们在选择哪家酒店时感到困惑。为了克服这个问题,研究人员试图创建一个推荐系统,帮助潜在的酒店居民根据他们的选择选择酒店。此外,它还可以通过其网站帮助企业增加酒店客房预订。在本研究中,研究人员将使用基于内容的过滤方法,使用术语频率-逆文档频率(TF-IDF)方法对文本数据进行加权,并使用余弦相似度方法测量文档相似度,在印度尼西亚的一家ota建立日惹酒店推荐系统。基于Good Karma日惹酒店推荐结果作为测试示例,得到10家相似的酒店,分别是Happy Buddha Yogyakarta - Hostel, Nextdoor Homestay, hotel Puspita, OYO 426 hotel Gading Resto, Omah Jegog Homestay, Prawirotaman Homestay, Prawirotaman附近的RedDoorz, Ayodhya Garden Hostel Yogyakarta by HOM, Bringin House Yogyakarta和House 24 Yogyakarta,余弦相似值为0.956666513,0.946570717,0.917459394,0.912534877,0.886439718,0.88221982。0.881775275, 0.875845794, 0.872030219,和0.871514859。
Hotel Recommendation System with Content-Based Filtering Approach (Case Study: Hotel in Yogyakarta on Nusatrip Website)
The increasing of Covid-19 pandemic has hampered people's activities, often causing stress if they are only stay at home continuously. This has led to an increasing trend of staycations or holiday activities in the city itself by renting a hotel. Hotel rental technology has begun to be transferred with the existence of OTA (Online Travel Agent). The existence of various kinds of hotels with various kinds of facilities that makes people feel confused in choosing which hotel to occupy. To help overcome this, the researchers tried to create a recommendation system to help prospective hotel residents choose the hotel according to their choice. In addition, it can also assist companies in increasing hotel room reservations through its website. In this study, researchers will build a hotel recommendation system in Yogyakarta at one of the OTAs in Indonesia using Content-Based Filtering Methods, weighting text data using Term Frequency-Inverse Document Frequency (TF-IDF) Methods and measuring document similarity using Cosine Similarity Methods. Based on the results of the Good Karma Yogyakarta hotel recommendations as a test example, 10 similar hotels were obtained, namely Happy Buddha Yogyakarta – Hostel, Nextdoor Homestay, Hotel Puspita, OYO 426 Hotel Gading Resto, Omah Jegog Homestay, Prawirotaman Homestay, RedDoorz near Prawirotaman, Ayodhya Garden Hostel Yogyakarta by HOM, Bringin House Yogyakarta, and House 24 Yogyakarta with cosine similarity values 0.956666513, 0.946570717, 0.917459394, 0.912534877, 0.886439718, 0.88221982, 0.881775275, 0.875845794, 0.872030219, and 0.871514859.