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 2022DO - 10.24843/JNATIA.2022.v01.i01.p34, 2022)
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%.