Yulianti, Devi (2023) Analisis Sentimen Kenaikan BBM Pada Twitter Menggunakan Metode Support Vector Machine (SVM). Undergraduate thesis, Politeknik Negeri Bengkalis.
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Abstract
Social Media Twitter has a large number of users in Indonesia. These users often generate a lot of tweets from various things such as: Entertainment, education, politics, and also work. One of the issues that has become a trending topic on Twitter in 2022 is the increase in fuel prices. This problem makes Twitter users make various tweets regarding the increase in fuel prices. For its classification, it uses the Support Vector Machine (SVM) method, which is one of the methods in Supervised Learning that is used to carry out classification. In sentiment analysis using the support vectore machine method, it is done by classifying sentiment into positive sentiment or negative sentiment. The level of accuracy of sentiment analysis on fuel price increases using the support vectore machine method is 83% using 800 training data and 200 test data.
| Item Type: | Thesis (Undergraduate) | ||||||||
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| Uncontrolled Keywords: | Twitter, SVM, Sentiment Analysis | ||||||||
| Subjects: | 410 ILMU TEKNIK > 450 TEKNIK ELEKTRO DAN INFORMATIKA > 463 Teknik Perangkat Lunak | ||||||||
| Divisions: | Jurusan Teknik Informatika > Sarjana Terapan Rekayasa Perangkat Lunak > TUGAS AKHIR | ||||||||
| Depositing User: | RPL A | ||||||||
| Date Deposited: | 12 Sep 2023 11:04 | ||||||||
| Last Modified: | 12 Sep 2023 11:04 | ||||||||
| URI: | http://eprints.polbeng.ac.id/id/eprint/10639 |
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