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All Journal Journal of Bionursing
Ajeng Ayu Kustianti
Jurusan Keperawatan, Sekolah Tinggi Ilmu Kesehatan Mitra Keluarga
Religion Biochemistry, Genetics & Molecular Biology Health Professions Nursing Public Health

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Teknologi Informasi Efektif Mendeteksi Cyberbullying Ajeng Ayu Kustianti; Renta Sianturi; Ameliya Sarwani; Anggita Putri Siswadi; Delia Nurmalita; Elisa Puspitasari
Journal of Bionursing Vol 4 No 2 (2022): Journal of Bionursing
Publisher : Fakultas Ilmu-ilmu Kesehatan Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (266.115 KB) | DOI: 10.20884/1.bion.2022.4.2.134

Abstract

Social media users are at risk for mental health disorders. Mental health problems can occur with cyberbullying. Cyberbullying that occurs on social media is in the form of rude comments, threats, insults, slander and even harassment given by netizens. Cyberbullying can shake a person's mental health condition and even have an impact on suicide. Cyberbullying will be very detrimental both mentally and productively. Cyberbullying must be detected early to prevent adverse effects on social media users. With advances in technology, it can be used to detect cyberbullying that occurs on social media. This article uses a literature review method approach, namely narrative literature review of 10 articles on the use of technology for cyberbullying detection in the period 2011 - 2021 with the aim of finding out cyberbullying comments on someone's account/post. Therefore, cyberbullying detection tries to collect global datasets on social media (Facebook, Instagram, Twitter, etc.), by classifying the Machine Learning method. Each algorithm method is evaluated using accuracy, precision, recall, and F1 score to determine the performance of the classification level
Co-Authors Ameliya Sarwani Anggita Putri Siswadi Delia Nurmalita Elisa Puspitasari Sianturi, Renta