Suharsono, Teguh Nurhadi and Fauzan, Ahmad and Mardiati, Rina (2022) Sentiment analysis of Covid-19 on Indonesian Twitter by implementing the Naive Bayes Method. In: 2022 8th International Conference on Wireless and Telematics (ICWT).
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Abstract
Twitter is one of the social media used in Indonesia to express opinions/opinions. One of them is the opinion about Covid-19 which is taking the world by storm. The government's provisions regarding Covid-19 itself reap many pros and cons on social media, one of which is Twitter. In this study, "Covid-19" will be used as a keyword to conduct sentiment analysis. Sentiment analysis is the process of understanding, extracting and processing textual data automatically to obtain information contained in an opinion sentence. The Naïve Bayes Classifier method is used to classify and calculate the total accuracy of the class that has been obtained. Based on the results from the kaggle dataset, there are a total of 2269 tweet documents with the keyword "Covid-19" on March 23 - May 14, 2020 which can be trusted because the data has been labeled by experts. The Naïve Bayes Classifier method has 2269 data sets, then divides it into 1815 training data, and 453 data testing data and produces an accuracy of 0.674
| Item Type: | Conference or Workshop Item (Paper) |
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| Uncontrolled Keywords: | Sentiment Analysis; Social Media; Twitter; Covid 19; Naïve Bayes |
| Subjects: | Engineering |
| Divisions: | Fakultas Sains dan Teknologi > Program Studi Teknik Elektro |
| Depositing User: | Rina Mardiati |
| Date Deposited: | 23 May 2023 05:10 |
| Last Modified: | 23 May 2023 05:10 |
| URI: | https://etheses.uinsgd.ac.id/id/eprint/67479 |
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