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All Journal G-Tech : Jurnal Teknologi Terapan
Ripa'i, Asep
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Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

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Journal : G-Tech : Jurnal Teknologi Terapan

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Deteksi Berita Hoax dengan Perbandingan Website Menggunakan Pendekatan Deep Learning Algoritma BERT Ripa'i, Asep; Santoso, Firman; Lazim, Farihin
G-Tech: Jurnal Teknologi Terapan Vol 8 No 3 (2024): G-Tech, Vol. 8 No. 3 Juli 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i3.4541

Abstract

Hoax news is false and misleading information that can cause provocation and hatred for readers. With easy internet access, the spread of hoax news is getting more massive. Therefore, there needs to be a method that can detect hoax news. The research uses deep learning methods by integrating text mining to find information and news patterns related to hoaxes. By using a dataset from the kaggle site totaling around 2700 then text preprocessing is carried out so that the data is more structured for further processing. Then make feature engineering from BERT so that the data can be processed by machine learning with three classification methods namely BERT, SVM and random forest then testing and evaluation. In this study, the model that produces the highest performance is BERT with (accuracy = 0.99, ROC-AUC = 0.99) compared to traditional machine learning models.
Co-Authors Lazim, Farihin Santoso, Firman