I. Saputra, Rahmad Singgih AJI PAMBUDI, Hanafi Eko Darono, Fachri Amsury, Muhammad Rizki Fahdia, Benni Ramadhan, Anggi Ardiansyah
{"title":"Analisis Sentimen Pengguna Marketplace Bukalapak dan Tokopedia di Twitter Menggunakan Machine Learning","authors":"I. Saputra, Rahmad Singgih AJI PAMBUDI, Hanafi Eko Darono, Fachri Amsury, Muhammad Rizki Fahdia, Benni Ramadhan, Anggi Ardiansyah","doi":"10.30998/faktorexacta.v13i4.7074","DOIUrl":null,"url":null,"abstract":"Received Sep 9, 2019 Revised May 20, 2020 Accepted December 27, 2020 A collection of tweets from Twitter users about Marketplace Bukalapak and Tokopedia can be used as a sentiment analysis. The data obtained is processed using data mining techniques, in which there is a process of mining the text, tokenize, transformation, classification, stem, etc. Then calculated into three different algorithms to be compared, the algorithm used is the Decision Tree, K-NN, and Naïve Bayes Classifier with the aim of finding the best accuracy. Rapidminer application is also used to facilitate writers in processing data. The highest results from this study are Decision Tree algorithm with 82% accuracy, 81.95% precision and 86% recall.","PeriodicalId":53004,"journal":{"name":"Faktor Exacta","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Faktor Exacta","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30998/faktorexacta.v13i4.7074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Received Sep 9, 2019 Revised May 20, 2020 Accepted December 27, 2020 A collection of tweets from Twitter users about Marketplace Bukalapak and Tokopedia can be used as a sentiment analysis. The data obtained is processed using data mining techniques, in which there is a process of mining the text, tokenize, transformation, classification, stem, etc. Then calculated into three different algorithms to be compared, the algorithm used is the Decision Tree, K-NN, and Naïve Bayes Classifier with the aim of finding the best accuracy. Rapidminer application is also used to facilitate writers in processing data. The highest results from this study are Decision Tree algorithm with 82% accuracy, 81.95% precision and 86% recall.
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