SENTIMENT ANALYSIS ON TWITTER OF PSBB EFFECT USING MACHINE LEARNING

  • Irwansyah Saputra (1*) STMIK Nusa Mandiri
  • Jose Andrean Halomoan (2) Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri
  • Adam Bagusmugi Raharjo (3) Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri
  • Cyra Rezky Ananda Syavira (4) Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri

  • (*) Corresponding Author
Keywords: twitter,, data mining,, analisis sentimen,, KNN, Decision Tree Algorithm

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%.

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Published
2020-09-15
How to Cite
Saputra, I., Halomoan, J., Raharjo, A., & Syavira, C. (2020). SENTIMENT ANALYSIS ON TWITTER OF PSBB EFFECT USING MACHINE LEARNING. Techno Nusa Mandiri : Journal of Computing and Information Technology, 17(2), 143-150. https://doi.org/10.33480/techno.v17i2.1635
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