Cyberbullying Prediction As Cyber Counseling Tools With Data Mining Classification

Agus Pamuji, Heri Satria Setiawan


The growth of data and information has been growing rapidly while the users of information technology devices continues to increase. Moreover, the ease of access to information is supported by the presence of mobile communications technology virtually owned by each user. Currently, there is a significant increase in the number of users, which would be considered as having the opportunity for the presence of cyber crime, especially in the case of bullying. In this study, we have investigated and predicted the tendency of bullying by using a data mining approach. As for the analysis of the case studies presented and their technical implementation through a data mining approach, there are several techniques were carried out in the classification of three classes, namely no potential for bullying, violence and insults. Thus, three classes were detected based on the results of the investigation and several techniques were evaluated by utilizing a comparison of the performance of each technique. The final results will represent which techniques are the best performing and have bold factors that have a potential tendency to cyberbullying would have recommended as a follow-up for cybercounseling tools.


Cyberbullying; Data Mining; Cybercounseling; Social Media; Information Technology

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