基于机器学习的情绪分析开放包市场用户和推特上的Tokopedia

I. Saputra, Rahmad Singgih AJI PAMBUDI, Hanafi Eko Darono, Fachri Amsury, Muhammad Rizki Fahdia, Benni Ramadhan, Anggi Ardiansyah
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引用次数: 2

摘要

收到日期:2019年9月9日修订日期:2020年5月20日接受日期:2020月27日推特用户关于Marketplace Bukalapak和Tokopedia的推文集合可用于情绪分析。使用数据挖掘技术对获得的数据进行处理,其中包括文本挖掘、标记化、转换、分类、词干等过程。然后计算出三种不同的算法进行比较,所使用的算法是决策树、K-NN和朴素贝叶斯分类器,目的是找到最佳精度。Rapidminer应用程序还用于方便写入程序处理数据。本研究的最高结果是决策树算法,其准确率为82%,准确率为81.95%,召回率为86%。
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Analisis Sentimen Pengguna Marketplace Bukalapak dan Tokopedia di Twitter Menggunakan Machine Learning
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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