Klasifikasi Tweet Cyberbullying di Aplikasi X dengan Algoritma Naïve Bayes
DOI:
https://doi.org/10.33795/jip.v12i1.8992Abstract
Perkembangan media sosial telah memberikan pengaruh yang signifikan dalam membentuk pola komunikasi dan interaksi masyarakat modern. Di balik manfaat yang ditawarkan, media sosial juga menjadi ruang terbuka bagi munculnya konten negatif, salah satunya adalah cyberbullying. Penelitian ini bertujuan untuk mengembangkan sistem klasifikasi dua tahap guna mendeteksi serta mengidentifikasi bentuk-bentuk cyberbullying dalam tweet berbahasa Indonesia. Data dikumpulkan melalui proses crawling berbasis autentikasi sesi pengguna (auth token) dengan pendekatan kata kunci tertentu. Metode yang digunakan meliputi pra-pemrosesan data teks, ekstraksi fitur menggunakan Term Frequency-Inverse Document Frequency (TF-IDF), serta pelatihan model klasifikasi menggunakan algoritma Multinomial Naïve Bayes. Pada tahap pertama, dilakukan klasifikasi biner untuk membedakan antara tweet yang mengandung unsur cyberbullying dan yang tidak, dengan akurasi mencapai 95%. Tahap kedua merupakan klasifikasi multikelas terhadap enam kategori cyberbullying, yaitu pelecehan, penghinaan, kata kasar, body shaming, ancaman, ambiguitas dan SARA, yang menghasilkan akurasi sebesar 82%. Seluruh hasil klasifikasi divisualisasikan secara interaktif melalui aplikasi web berbasis Python Flask. Hasil penelitian ini menunjukkan bahwa pendekatan dua tahap klasifikasi dengan algoritma Naïve Bayes mampu mengidentifikasi konten cyberbullying secara efektif, serta berpotensi digunakan sebagai salah satu alat bantu untuk mendukung upaya pencegahan perundungan daring di media sosial.
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