Deteksi Berita Online Hoax Covid-19 Di Indonesia Menggunakan Metode Hybrid Long Short Term Memory dan Support Vector Machine
Submission Date: 2022-02-09 21:11:00
Accepted Date: 2023-03-14 00:00:00
Abstract
Fokus masyarakat Indonesia tidak lepas dari kasus pandemi Coronavirus Disease 2019 (COVID-19) dengan mengikuti setiap informasi terkait perkembangannya setiap hari. Hal ini yang mendorong banyak pihak terlebih pemerintah untuk menyediakan layanan informasi terkini terkait COVID-19. Namun, banyak berita online menyajikan informasi palsu yang dikenal dengan berita hoax tentang COVID-19 yang dapat menyebabkan keresahan masyarakat. Pada Tugas Akhir ini, dilakukan deteksi terhadap berita–berita online seputar informasi COVID-19 di Indonesia yang dibagi menjadi dua kategori, yaitu berita hoax dan berita fakta. Proses deteksi berita online dilakukan dengan metode penggabungan Long-Short Term Memory dan Support Vector Machine (hybrid LSTM-SVM). LSTM menghasilkan fitur teks representatif yang selanjutnya digunakan untuk proses klasifikasi berita oleh SVM yang menghasilkan persentase nilai akurasi mencapai 94%. Nilai tersebut lebih tinggi dibandingkan dengan hanya mengimplementasikan Metode LSTM atau Metode SVM saja.
Keywords
COVID-19; Deteksi Berita Hoax; LSTM; SVM
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