Rivanie, Tri and Pebrianto, Rangga and Hidayat, Taopik and Bayhaqy, Achmad and Gata, Windu and Novitasari, Hafifah Bella (2021) ANALISIS SENTIMEN TERHADAP KINERJA MENTERI KESEHATAN INDONESIA SELAMA PANDEMI COVID-19. Jurnal Informatika, 21 (1).
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Abstract
ABSTRACT The pandemic that occurred in Indonesia has not yet subsided and far from under control. Indonesian Ministry of Health is most appropriate person to responsible for providing an explanation of actual situation and extent to which state has handled it. However, he has rarely appeared in public lately to explain about handling of Covid-19 pandemic. In response, many people are pros and cons come to give their opinions and feedback. The increasing use of internet during pandemic, especially on social media, where one of them is Twitter, which is a means of expressing opinions. Posting tweets is a community habit to assess or respond to events, as well as represent public's response to an event, especially Ministry of Health steps and policies in handling and breaking chain of Covid-19 pandemic. The tweet posts were taken only in Indonesian-language and also related to performance of Government, especially Ministry of Health. After that, a label is given so that sentiment of tweets is known. To test results of these sentiments, an algorithm is used by comparing two methods of Support Vector Machine (SVM) and Naïve Bayes (NB). Validation was carried out using k-Fold Cross Validation to obtain an accuracy value. The results show that accuracy value for NB algorithm is 66.45% and SVM algorithm has a greater accuracy value of 72.57%. So it can be seen that SVM algorithm managed to get the best accuracy value in classifying positive comments and negative comments related to sentiment analysis towards Ministry of Health.
| Item Type: | Article |
|---|---|
| Subjects: | Ilmu Komputer |
| Divisions: | Jurnal > Jurnal Ilmu Komputer |
| Depositing User: | Editor |
| Date Deposited: | 10 Aug 2022 08:39 |
| Last Modified: | 02 Feb 2023 07:03 |
| URI: | http://repo.darmajaya.ac.id/id/eprint/7990 |
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