SciRepID - Deteksi Cyberbullying pada Pemain Sepak Bola di Platform Media Sosial “X” Menggunakan Metode Long Short-Term Memory (LSTM)


Deteksi Cyberbullying pada Pemain Sepak Bola di Platform Media Sosial “X” Menggunakan Metode Long Short-Term Memory (LSTM)

Repeater : Publikasi Teknik Informatika dan Jaringan
Asosiasi Riset Teknik Elektro dan Informatika Indonesia (ARTEII)

📄 Abstract

Social media has become a crucial part of modern life around the globe, providing users with various conveniences. However, its widespread use has also brought about new challenges, one of which is cyberbullying. This harmful issue can have serious emotional and physical effects on those targeted. Cyberbullying occurs in many areas, including sports, and soccer—a sport loved by millions—is no exception. Soccer players often face severe criticism, hate speech, and harassment on social media platforms. To tackle this problem, this study aims to create a strong model for detecting cyberbullying on the social media platform “X” using the Long Short-Term Memory (LSTM) method. By utilizing advanced machine learning techniques, the proposed model intends to identify and reduce instances of cyberbullying, helping to create a safer online space for athletes and the wider community.

🔖 Keywords

#Cyberbulliying Detecttion; Football Player; Social Media; Long Short-Term Memory; LSTM

ℹ️ Informasi Publikasi

Tanggal Publikasi
31 January 2025
Volume / Nomor / Tahun
Volume 3, Nomor 1, Tahun 2025

📝 HOW TO CITE

Pawit Widiyantoro; Paradise Paradise; Yogo Dwi Prasetyo, "Deteksi Cyberbullying pada Pemain Sepak Bola di Platform Media Sosial “X” Menggunakan Metode Long Short-Term Memory (LSTM)," Repeater : Publikasi Teknik Informatika dan Jaringan, vol. 3, no. 1, Jan. 2025.

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