Cosmetic Product Review Sentiment Using K-Nearest Neighbor

Nuraini, Pandu Pratama Putra, Andi Supriadi Chan
{"title":"Cosmetic Product Review Sentiment Using K-Nearest Neighbor","authors":"Nuraini, Pandu Pratama Putra, Andi Supriadi Chan","doi":"10.53893/ijrvocas.v3i4.83","DOIUrl":null,"url":null,"abstract":"Indonesia, with a population of about 250 million, is a promising market for cosmetics companies. Aiming for women as the main target group for consumers, most of the cosmetics industry has recently begun to innovate  products for men (Ministry of Industry, Republic of Indonesia, 2013). According to  the  Indonesian Cosmetics Companies Association (Perkosmi) of the Ministry of Industry of the Republic of Indonesia,  sales of imported cosmetics reached IDR 2.44 trillion in 2012, an increase of 30% compared to IDR 1.87 trillion in 2011. In 2013, sales of imported cosmetics are expected to increase by another 30% to Rs 3.17 trillion. One of the most popular cosmetics is the MS Glow brand. MS Glow is an acronym for Magic For Skin,  the brand's motto, which reflects Indonesia's most brilliant products. The data is  from WebFemaleDaily, where users review Indonesian MS Glow cosmetics. The results of the analysis are intended to determine the positive and negative reactions of users of MS Glow cosmetics. The classification process uses the K-nearest neighbor (K-NN) algorithm. The accuracy value of K-NN with k = 1 is obtained from the result of 63.64% confusion matrix test.","PeriodicalId":14205,"journal":{"name":"International Journal of Research in Vocational Studies (IJRVOCAS)","volume":"304 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Research in Vocational Studies (IJRVOCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53893/ijrvocas.v3i4.83","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Indonesia, with a population of about 250 million, is a promising market for cosmetics companies. Aiming for women as the main target group for consumers, most of the cosmetics industry has recently begun to innovate  products for men (Ministry of Industry, Republic of Indonesia, 2013). According to  the  Indonesian Cosmetics Companies Association (Perkosmi) of the Ministry of Industry of the Republic of Indonesia,  sales of imported cosmetics reached IDR 2.44 trillion in 2012, an increase of 30% compared to IDR 1.87 trillion in 2011. In 2013, sales of imported cosmetics are expected to increase by another 30% to Rs 3.17 trillion. One of the most popular cosmetics is the MS Glow brand. MS Glow is an acronym for Magic For Skin,  the brand's motto, which reflects Indonesia's most brilliant products. The data is  from WebFemaleDaily, where users review Indonesian MS Glow cosmetics. The results of the analysis are intended to determine the positive and negative reactions of users of MS Glow cosmetics. The classification process uses the K-nearest neighbor (K-NN) algorithm. The accuracy value of K-NN with k = 1 is obtained from the result of 63.64% confusion matrix test.
利用 K 最近邻法分析化妆品评论情感
印度尼西亚拥有约2.5亿人口,对化妆品公司而言是一个前景广阔的市场。在以女性为主要目标消费群体的同时,大多数化妆品行业最近开始创新男性产品(印度尼西亚共和国工业部,2013年)。根据印度尼西亚共和国工业部印度尼西亚化妆品公司协会(Perkosmi)的数据,2012 年进口化妆品的销售额达到 2.44 万亿印尼盾,与 2011 年的 1.87 万亿印尼盾相比增长了 30%。2013 年,进口化妆品的销售额预计将再增长 30%,达到 3.17 万亿印尼盾。MS Glow 品牌是最受欢迎的化妆品之一。MS Glow是Magic For Skin的缩写,是该品牌的座右铭,反映了印尼最出色的产品。数据来自 WebFemaleDaily,用户通过该网站对印尼 MS Glow 化妆品进行评论。分析结果旨在确定用户对 MS Glow 化妆品的积极和消极反应。分类过程采用 K 近邻(K-NN)算法。K-NN 算法(K = 1)的准确度值由 63.64% 的混淆矩阵测试结果得出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信