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

Tsania Maulidia Wijiasih, Rona Nisa Sofia Amriza, Dedy Agung Prabowo

Abstract


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%.

Keywords


Support Vector Machine; DASS 21; Depression; Anxiety; Stress; Facebook

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DOI: https://doi.org/10.31326/jisa.v5i1.1273

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Copyright (c) 2022 Tsania Maulidia Wijiasih, Rona Nisa Sofia Amriza, Dedy Agung Prabowo

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JOURNAL IDENTITY

Journal Name: JISA (Jurnal Informatika dan Sains)
e-ISSN: 2614-8404, p-ISSN: 2776-3234
Publisher: Program Studi Teknik Informatika Universitas Trilogi
Publication Schedule: June and December 
Language: Indonesia & English
APC: The Journal Charges Fees for Publishing 
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OAI addresshttp://trilogi.ac.id/journal/ks/index.php/JISA/oai
Contactjisa@trilogi.ac.id
Sponsored by: DOI – Digital Object Identifier Crossref, Universitas Trilogi, Yayasan Damandiri

In Collaboration With: Indonesian Artificial Intelligent Ecosystem(IAIE), Relawan Jurnal IndonesiaJurnal Teknologi dan Sistem Komputer (JTSiskom)

 

 


JISA (Jurnal Informatika dan Sains) is Published by Program Studi Teknik Informatika, Universitas Trilogi under Creative Commons Attribution-ShareAlike 4.0 International License.