The Classification of Anxiety, Depression, and Stress on Facebook Users Using the Support Vector Machine

Wijiasih, Tsania Maulidia and Amariza, Rona Nisa Sofia and Prabowo, Dedy Agung The Classification of Anxiety, Depression, and Stress on Facebook Users Using the Support Vector Machine. The Classification of Anxiety, Depression, and Stress on Facebook Users Using the Support Vector Machine, 5 (1). pp. 75-79. ISSN 2614-8404

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Abstract

The Classification of Anxiety, Depression, and Stress on Facebook Users Using the Support Vector Machine 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%

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