Perbandingan performa deteksi cyberbullying dengan transformer, deep learning, dan machine learning
DOI:
https://doi.org/10.31571/saintek.v13i1.4002Keywords:
Transformers, Sentiment Analysis, Natural Language Processing, Deep LearningAbstract
Peningkatan aktivitas browsing terutama di situs media sosial mengakibatkan rawannya terjadi cyberbullying (perundungan dunia maya). Telah banyak dilakukan penelitian untuk melakukan pendeteksian cyberbullying, baik dengan metode machine learning maupun deep learning. Dalam penelitian ini dilakukan perbandingan performa pengklasifikasian data teks apakah termasuk cyberbullying atau bukan, dengan menggunakan algoritma Transformer. Kemudian dilakukan perbandingan performa metode transformer dengan metode deep learning lain (RNN, LSTM, dan GRU) serta dengan metode machine learning (Naïve Bayes, Logistic Regression, SVM, dan Decision Tree). Hasil terbaik untuk model deep learning adalah dataset Youtube dengan model Transformer yang mendapat akurasi 98.49%. Kemudian hasil terbaik model machine learning adalah dataset Youtube dengan model SVM dan menggunakan feature Tf-Idf yang mendapat akurasi 97.82%.
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