Sentiment Analysis of Indonesia Presidency Election 2019 on Twitter Based on Geolocation Using Naïve Bayesian Classification Method

Authors

  • Wiranto Horsen Silitonga PT. Bank OCBC NISP
  • Jay Idoan Sihotang Fakultas Teknologi Informasi, Universitas Advent Indonesia

https://doi.org/10.36342/teika.v9i02.2199

Keywords:

Sentiment Analysis, Indonesia Presidency Election, Jokowi, Prabowo, Geolocation, Datamining, Naïve Bayesian Classifier, Multinominal Naïve Bayes

Abstract

2019 Indonesian Presidential Election is crowded to be discussed in the real world and also cyberspace, specifically on Twitter. Everyone is free to agree on the 2019 Indonesian Presidential candidate pair. Opinion raises many opinions, not only positive or neutral opinions but there are also negative opinions. Twitter's is now one of the most effective and efficient promotional or campaign venues to attract supporters. In this case, the researcher will conduct research on community leaders who are running for the presidency of Indonesia. The research method used in this study is the Naïve Bayesian Classifier classification algorithm. The data used are Indonesian tweets with Jokowi (# Jokowi2Periode) and Prabowo (#PrabowoSandi) keywords totaling 1009 data tweets for 5 months starting from September 1, 2019 to 31 January 1, 2019. Indonesia, namely Jakarta, Bandung, Medan, and Surabaya. Each data will be taken manually by using the Geolocation API that has been provided by Twitter via a Twitter search. The results of the classification using the Naïve Bayesian Classifier algorithm received 839 positive tweets, 32 negative tweets, and 67 neutral tweets from 938 overall tweets, or in the form of a percentage, there were 90% containing positive sentimen, 3% negative, and 7% negative sentimen towards Mr. Joko Widodo. And 56 positive tweets, 6 negative tweets, and 8 neutral tweets from 70 overall tweets, or in the form of the percentage there are 80% positive sentimens, 9% negative sentimens, and 11% neutral sentimens towards Mr. Prabowo. The level of accuracy generated from the Naïve Bayesian Classifier algorithm itself for this study amounted to 77.62%.

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Author Biography

Jay Idoan Sihotang, Fakultas Teknologi Informasi, Universitas Advent Indonesia

Graduate Student, Sekolah Tinggi Elektro dan Informasi, Institut Teknologi Bandung

References

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Published

2019-10-31

How to Cite

Silitonga, W. H., & Sihotang, J. I. (2019). Sentiment Analysis of Indonesia Presidency Election 2019 on Twitter Based on Geolocation Using Naïve Bayesian Classification Method. TeIKa, 9(2), 115-127. https://doi.org/10.36342/teika.v9i02.2199

Issue

Vol. 9 No. 2 (2019): TeIKa: October 2019

Section

Datamining

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