The Classification of Anxiety, Depression, and Stress on Facebook Users Using the Support Vector Machine
| Autor: | Tsania Maulidia Wijiasih, Rona Nisa Sofia Amriza, Dedy Agung Prabowo |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | JISA (Jurnal Informatika dan Sains), Vol 5, Iss 1, Pp 75-79 (2022) |
| Druh dokumentu: | article |
| ISSN: | 2776-3234 2614-8404 |
| DOI: | 10.31326/jisa.v5i1.1273 |
| Popis: | Social media remains an essential platform for connecting people with friends, family, and the world around them. However, when events spread on social media are primarily negative, it will cause depression, anxiety, and stress that tend to increase. This study aims to classify depression, anxiety, and stress using the Support Vector Machine. The data in this study were obtained from active Facebook users using the Depression Anxiety Stress Scale (DASS 21) questionnaire. This study adopted the Knowledge Discover Database process. The result of this study is an evaluation of the performance of the Support Vector Machine classification of depression, anxiety, and stress. The accuracy of the Support Vector Machine in this study is 98.96%. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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