Sentiment Analysis of Public Responses on Social Media to Satire Joke Using Naive Bayes and KNN

Authors

  • Rasyid Ihsan Putra Selian Informatics Department, Universitas Dr. Soetomo, Surabaya, Indonesia
  • Anik Vega Vitianingsih Informatics Department, Universitas Dr. Soetomo, Surabaya, Indonesia
  • Slamet Kacung Informatics Department, Universitas Dr. Soetomo, Surabaya, Indonesia
  • Anastasia Lidya Maukar Industrial Engineering Department, President University, Bekasi, Indonesia
  • Jack Febrian Rusdi Informatics Department, Sekolah Tinggi Teknologi Bandung, Bandung, Indonesia

DOI:

10.33395/sinkron.v8i3.13721

Keywords:

Satire Joke, sentiment analysis, Naïve Bayes, Government criticism, social media

Abstract

This study examines the use of Satire Joke as a humorous communication style in conveying criticism of the government through social media. Satire Joke is often used to depict the government's inability to address important social issues, such as slow bureaucratic processes and unfulfilled political promises. The aim of this research is to analyze public sentiment towards Satire Joke expressed on the YouTube social media platform. The methods used in this study are Naïve Bayes and K-Nearest Neighbors (KNN) due to their effectiveness in data classification. The results of this study are expected to help gain an understanding of social issues for the community and public knowledge. This research is also expected to contribute to the development of sentiment analysis methods in the future. The analysis results show that 400 data have neutral sentiment, 850 data have negative sentiment, and 947 data have positive sentiment. Based on testing, both Naive Bayes and KNN methods show good performance. The Naive Bayes method achieved the best accuracy of 90.29%, while the KNN method achieved an accuracy of 60.75%.

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How to Cite

Putra Selian, R. I. ., Vitianingsih, A. V., Kacung, S. ., Lidya Maukar, A. ., & Febrian Rusdi, J. . (2024). Sentiment Analysis of Public Responses on Social Media to Satire Joke Using Naive Bayes and KNN. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 8(3), 1443-1451. https://doi.org/10.33395/sinkron.v8i3.13721

Issue

Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024

Section

Articles

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Copyright (c) 2024 Anik Vega Vitianingsih, Rasyid Ihsan Putra Selian, Slamet Kacung, Anastasia Lidya Maukar, Jack Febrian Rusdi

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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