Identifikasi Audio Ancaman Menggunakan Metode Convolutional Neural Network
DOI:
https://doi.org/10.26418/justin.v10i4.52433Keywords:
Convolutional Neural Network, Web Scraping, Audio, Speech Recognition, TextAbstract
Sosial media merupakan sebuah aplikasi yang berbasis internet dan dapat menunjang fungsi interaksi pada masyarakat. Berdasarkan data laporan yang diambil dari Kominfo, terdapat banyak konten negatif yang berisi ujaran kebencian. Berdasarkan masalah tersebut maka akan dibuat sebuah sistem yang bertujuan untuk mendeteksi ancaman terutama pada audio. Sehingga dapat mengurangi dan menyaring konten konten yang berisi suara ancaman. Pada proses pembuatan sistem pendeteksi maka dibutuhkan beberapa sampel data ancaman yang akan diolah. Pengumpulan data akan dilakukan dengan menggunakan Web Scraping pada sosial media twitter. Setelah terkumpul data akan dilakukan preprocessing. Pengolahan data akan menggunakan metode Convolutional Neural Network. Akurasi yang dihasilkan dengan menggunakan metode CNN tersebut adalah 82%. Model yang didapatkan dari metode tersebut akan digunakan sebagai bahan untuk melakukan prediksi audio ancaman. Audio ancaman akan dilakukan konversi menjadi teks menggunakan speech recognition yang kemudian akan dilakukan presiksi dengan menggunakan model tersebut. Hasil dari prediksi yang dilakukan menghasilkan output berupa ancaman atau bukan ancaman.References
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