@article{repository23433,
            year = {2022},
          volume = {5},
           title = {(JLK - S3) - Hasan, Sidik, Afikah  [2022-11-20]},
             doi = {https://doi.org/10.26418/jlk.v5i2.99},
          number = {2},
       publisher = {Indonesia Association of Computational Linguistics (INACL)},
         journal = {JLK: Jurnal Linguistik Komputasional},
           month = {November},
           pages = {71--76},
        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\%.},
             url = {https://inacl.id/journal/index.php/jlk/article/view/99},
          author = {Hasan, Firman Noor},
            issn = {2621-9336}
}