Lavenia, Nur Lickha (2023) Analisis Sentimen pada Media Sosial Twitter Terhadap Isu Gangguan Depresi dengan Menggunakan Metode Naive Bayes. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
Depression disorder is a serious issue in global mental health. This study analyzes sentiment related to depression disorder on Twitter using the Naïve Bayes method. This is essential because social media, especially Twitter, has become a significant platform for sharing feelings and emotions and influencing the mental well-being of society. The research involves the collection and processing of depression-related tweet data using the snscrape method. Three Naïve Bayes methods (Multinomial, Gaussian, Bernoulli) are compared to classify positive, negative, or neutral sentiments in tweets related to depression disorder on Twitter. The test results indicate that the Multinomial Naïve Bayes method has the highest accuracy rate in sentiment analysis related to depression disorder on Twitter, with an accuracy of 90.13%. The recommended approach is to use the Multinomial Naïve Bayes method as an effective way to classify sentiments of depression disorder on social media.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | Q Science > QA Mathematics > QA76.6 Computer Programming | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Information Systems | ||||||||||||
| Depositing User: | Nur Lickha Lavenia | ||||||||||||
| Date Deposited: | 27 Jul 2023 05:31 | ||||||||||||
| Last Modified: | 27 Jul 2023 05:31 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/16511 |
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