Pramudita, Yoga and , Dimas Aryo Anggoro S.Kom., M.Sc. (2024) Analisis Sentimen Mengenai Sandwich Generation Pada Media Sosial X/Twitter dengan Menerapkan Algoritma Support Vector Machine. Skripsi thesis, Universitas Muhammadiyah Surakarta.
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Abstract
Sandwich generation has to balance the responsibility of taking care of parents and children, they experience high levels of stress. The level of stress experienced by sandwich generation not only affects their relationship with loved ones, children and family, but also affects their own well-being. The sandwich generation vent by venturing directly with others or vent through social media. The Support Vector Machine (SVM) algorithm is a method that has the highest level of accuracy as evidenced by previous research related to this study. In this study, the sentiment of Twitter users regarding Sandwich Generation was analyzed using the Support Vector Machine (SVM) algorithm. The method calculated the value of tweet data, yielding an accuracy value of 88%, a high precision value, and strong recall for both classes. As for the sentiment results on the topic of Sandwich Generation on Twitter social media is classified as negative. The results of this research conducted by applying the Support Vector Machine (SVM) algorithm show that the results of sentiment analysis on Sandwich Generation on Twitter social media are negative.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | sentiment analysis, sandwich generation, support vector machine. |
| Subjects: | T Technology > TZ Technical Information > TA02 Software. Aplication > Pemograman |
| Divisions: | Fakultas Ilmu Komunikasi dan Informatika > Teknik Informatika |
| Depositing User: | YOGA PRAMUDITA |
| Date Deposited: | 11 Feb 2024 11:50 |
| Last Modified: | 11 Feb 2024 11:50 |
| URI: | http://eprints.ums.ac.id/id/eprint/121175 |
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