KLASIFIKASI CYBERBULLYING TWEET MENGGUNAKAN ALGORITMA SVM DAN XGBOOST
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This study aims to classify cyberbullying tweets using two machine learning approaches, namely the SVM and XGBoost algorithms. The input data used for analysis consists of randomly collected tweets that have been labeled, feature extraction, and model training and testing using both algorithms. The results of the experiment show that XGBoost performs slightly better in classifying cyberbullying tweets than SVM. These findings contribute to the development of classification methods for detecting cyberbullying on social media, which can help mitigate its negative impact. This study also shows the potential use of the XGBoost algorithm in the context of cyberbullying detection on various other social media platforms such as TikTok and Instagram.
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