Analysis Sentiment to Religious Based Issues Netizen Comments on President Jokowi 's Instagram using the Naive Bayes Classifier Method

  • Lingga Kurnia Ramadhani Universitas Ivet
  • Bajeng Nurul Widyaningrum Politeknik Bina Trada
Keywords: Data Mining, Naïve Bayes Classifier, Sentiment Analysis, Instagram

Abstract

The presence of Instagram is one of the most popular social media platforms. Make people make a habit of posting photo and video content. In this way, Instagram can become a source of public opinion and sentiment data, which data can be used for social studies. Social studies is still a crucial issue for countries today, including Indonesia, is a matter of religion. Apart from problems regarding religion, public sentiment can be researched from Instagram. The sentiment dataset related to religion is taken from public comments from President Joko Widodo's content regarding Merry Christmas Greetings and Visits to Churches. The analysis system will use sentiment analysis using a method from machine learning, namely the naive Bayes classifier to determine positive & negative sentiments. The comment dataset is 2,600 in which the positive and negative sentiment class datasets are determined manually by experts in the field of linguistics or communication totaling 1,309 to be used as training data. the results of testing the Naïve Bayes classifier training data with a total of 1309 obtained an accuracy prediction of 97.63% and test data where positive & negative sentiment classes had not been determined before hand amounted to 1291 in sentiment analysis obtained positive sentiment 70.56% & negative sentiment 29.44%.

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Published
2024-02-05
How to Cite
[1]
L. Kurnia Ramadhani and B. Nurul Widyaningrum, “Analysis Sentiment to Religious Based Issues Netizen Comments on President Jokowi ’s Instagram using the Naive Bayes Classifier Method”, JI, vol. 9, no. 1, pp. 59-66, Feb. 2024.