Analysis of Cyberbullying Level using Support Vector Machine Method - Purnayasa, Ngurah Indra; Suarjaya, I Made Agus Dwi; Dharmaadi, I Putu Arya (Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi); Vol 10 No 2 (2022): Vol. 10, No. 2, August 2022DO - 10.24843/JIM.2022.v10.i02.p01, 2022)
Internet users in Indonesia is increasing in every year. The increase caused by several factors, such as the increasingly even distribution of internet infrastructure in Indonesia. The internet has a positive impact such as facilitating communication between individuals, while the negative impact of the internet is intimidation to someone or known as cyberbullying. Cyberbullying has a huge impact on mental health person, causing victim to be angry, depressed, and anxious. This research aims to measure the level of cyberbullying in Indonesia on Twitter using TF-IDF and Support Vector Machine. Classification in this study is classified into two classes, namely cyberbullying and non-cyberbullying. Twitter data used in this study were 3,344,782 tweets that resulted in a cyberbullying classification level of 34.59% and a non-cyberbullying classification level of 65.41%. The best accuracy value obtained is 85%.