Analysis Sentiment of Community Response on Cooking Oil Price Increase Policy With Naive Bayes Classifier Algorithm

  • Firman Noor Hasan Universitas Muhammadiyah Prof. Dr. Hamka
  • Fajar Sidik Universitas Muhammadiyah Prof. Dr. Hamka
  • Prista Afikah Universitas Muhammadiyah Prof. Dr. Hamka

Abstract

Cooking oil is a basic need for Indonesian people. Indonesia experienced a shortage of oil in March 2022. This has become a hot conversation on Twitter social media last March, many people think positively or negatively. But behind it all there are different assessments of the parties who feel the pros and cons, various parties have different points of view. In this article, we conduct a sentiment analysis on the public's response to the scarcity of cooking oil using a dataset obtained from the Twitter digital platform. This article aims to classify tweets related to the scarcity of cooking oil into positive and negative sentiments using a machine learning strategy using the Naive Bayes method. This algorithm was chosen to make it easier for the public to make choices and to know the level of accuracy of the method, where the level of accuracy obtained from the nave Bayes classifier method 72%.

Author Biographies

Firman Noor Hasan, Universitas Muhammadiyah Prof. Dr. Hamka

Program Studi Teknik Informatika

Fajar Sidik, Universitas Muhammadiyah Prof. Dr. Hamka

Program Studi Teknik Informatika

Prista Afikah, Universitas Muhammadiyah Prof. Dr. Hamka

Program Studi Teknik Informatika

Published
2022-11-20
How to Cite
HASAN, Firman Noor; SIDIK, Fajar; AFIKAH, Prista. Analysis Sentiment of Community Response on Cooking Oil Price Increase Policy With Naive Bayes Classifier Algorithm. Jurnal Linguistik Komputasional, [S.l.], v. 5, n. 2, p. 71 - 76, nov. 2022. ISSN 2621-9336. Available at: <http://inacl.id/journal/index.php/jlk/article/view/99>. Date accessed: 29 jan. 2023. doi: https://doi.org/10.26418/jlk.v5i2.99.
Section
Articles