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All Journal Jurnal Nasional Teknologi Informasi dan Aplikasinya
Setiawan, Vinna
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Computer Science & IT

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Implementasi Algoritma Support Vector Machine dalam Deteksi Depresi Pada Twitter Setiawan, Vinna; Suhartana, I Ketut Gede
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Mental health is an important part of human life. Over time, mental health is getting more attention along with the increasing number of people who experience mental health disorders. For example, in the U.S., 1 in 5 adults has a mental health disorder, with 8% experiencing depression[1]. Social media, one of which is Twitter as a place for opinions and voices, is often a place for people to convey what they feel. Therefore, writings posted on twitter can be an option to detect a person's mental health, namely depression. To classify between writings that have the characteristics of depression and not, the Support Vector Machine method is used. Based on testing on the Support Vector Machine method for depression classification, the highest accuracy value was obtained at 85,6%.
Co-Authors I Ketut Gede Suhartana