Prediksi Ujaran Kebencian Berbasis Text Pada Sosial Media Menggunakan Metode Neural Network

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Kristiawan Nugroho
Endang Tjahjaningsih
Lie Liana
Raden Mohamad Herdian Bhakti


Currently information technology has helped in various forms of human life. They can communicate with each other through various electronic media, including using social media. The number of social media users is increasing from year to year in Indonesia. However, the development of the use of social media has also resulted in various problems, including hate speech, which will eventually lead to legal consequences. Various methods have been taken to limit the development of hate speech, including by blocking users who write hate speech on social media applications. Limiting the use of social media for hate speech can be more optimally carried out by detecting text-based words that have the potential to become hate speech. This study uses the Neural Network (NN) method to predict words that contain hatespeech on social media with an accuracy rate of 73% better than other methods such as Decission Tree and K-Nearest Neighbor (KNN) which only achieve an accuracy rate of 68.5 %.

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How to Cite
Nugroho, K., Tjahjaningsih, E. ., Liana , L. ., & Mohamad Herdian Bhakti, R. . (2023). Prediksi Ujaran Kebencian Berbasis Text Pada Sosial Media Menggunakan Metode Neural Network. Jurnal Ilmiah Intech : Information Technology Journal of UMUS, 5(1), 60–68.


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