Deteksi Cyberbullying berdasarkan Unsur Perbuatan Pidana yang Dilanggar dengan Naive Bayes dan Support Vector Machine - Manoppo, Tommy Nugraha; Fudholi, Dhomas Hatta (J-SAKTI (Jurnal Sains Komputer dan Informatika), 2021)
Lack of understanding by Indonesian social media user about law impact inflicted to cyberbullying perpetrators makes many cyberbullying cases has not handled properly and ended up with nothing. Indonesia hasn’t yet law authority that govern cyberbullying in specific, causing no guideline regard the definition about cyberbullying itself. There is an extension about definition of violence which state that violence is not only physically deliver, but also psychologically, referred an inferences cyberbullying characteristics possibly qualify in element of criminal act. Therefore, the element of criminal act can be used as a basis for detecting potential of cyberbullying. In this research, literature review is used to determine the elements of criminal acts related to the characteristics of cyberbullying and also in finding a model classifier to detect cyberbullying messages. So there are 5 criminal acts related to cyberbullying characteristic which insult, accuse with defamation, hatred about ethnicity, religion, race and inter-group relations, threat of violence, and threat of telling secret. Total of 5000 tweets are collected as a dataset. Feature extraction, using the N-gram method with TF-IDF weighting is expected to obtain sentiment based on the use of words. The context of language becomes important in this study, so the dataset annotation process is carried out by linguist. The results on the application of the two model classfier were Naïve Bayes and SVM after applying resampling by over-sampling using SMOTE method, can correctly predict the potential for cyberbullying by their violated element of criminal act with the average performance measurement of 90%.