Sentiment Analysis of Cyberbullying on Instagram User Comments

Instagram is a social media for sharing images, photos and videos. Instagram has many active users from various circles. In addition to sharing submissions, Instagram users can also give likes and comments to other users' posts. However, the comment feature is often misused, for example it is used for cyberbullying which includes one act against the law. But until now, Instagram still does not provide a feature to detect cyberbullying. Therefore, this study aims to create a system that can classify comments whether they contain elements of cyberbullying or not. The results of the classification will be used to detect cyberbullying comments. The algorithm used for classification is Naïve Bayes Classifier. Then for each comment will pass the preprocessing and feature extraction stages with the TF-IDF method. For evaluation and testing using the K-Fold Cross Validation method. The experiment is divided into two, namely using stemming and without stemming. The training data used is 455 data. The best experimental results obtained an accuracy of 84% both with stemming, and without stemming.