Surabaya Government Performance Evaluation Using Tweet Analysis

Authors

  • Kartika Fithriasari Institut Teknologi Sepuluh Nopember
  • Rakhmah Wahyu Mayasari Institut Teknologi Sepuluh Nopember
  • Nur Iriawan Institut Teknologi Sepuluh Nopember
  • Wiwiek Setya Winahju Institut Teknologi Sepuluh Nopember

DOI:

https://doi.org/10.11113/matematika.v36.n1.1176

Abstract

The purpose of this research is to determine the various positive attributes appreciated by the public, and the negative things that need to be improved by the Surabaya government. The sentiment analysis methods, including the Naïve Bayes Classifier, Support Vector Machine, and Logistic Regression, are employed to classify the pros and cons of the Surabaya government. The comparison of the three methods demonstrated that SVM gives the best classification accuracy compared to others. Police performance is the highlighted word in the positive category, while traffic congestion is in the negative.

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Published

2020-03-31

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Section

Articles