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All Journal Techno Nusa Mandiri : Journal of Computing and Information Technology
Jose Andrean Halomoan
Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri
Computer Science & IT

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SENTIMENT ANALYSIS ON TWITTER OF PSBB EFFECT USING MACHINE LEARNING Irwansyah Saputra; Jose Andrean Halomoan; Adam Bagusmugi Raharjo; Cyra Rezky Ananda Syavira
Jurnal Techno Nusa Mandiri Vol 17 No 2 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v17i2.1635

Abstract

A collection of tweets from Twitter users about PSBB can be used as sentiment analysis. The data obtained is processed using data mining techniques (data mining), 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 to find the best accuracy. Rapidminer application is also used to facilitate writers in processing data. The highest results from this study were the Decision Tree algorithm with an accuracy of 83.3%, precision 79%, and recall 87.17%.
Co-Authors Adam Bagusmugi Raharjo Cyra Rezky Ananda Syavira Irwansyah Saputra