Jurnal Bangkit Indonesia
Vol 10 No 02 (2020): Bulan Oktober 2020

Identifikasi Berita Hoax dengan Recurrent Neural Network

Kevin Perdana (Unknown)
Zulfachmi (Unknown)
Dwi Nurul Huda (Unknown)



Article Info

Publish Date
10 Oct 2020

Abstract

The problem of hoax news is something universal that can change someone perspective. The impact can generate fear, racism ideas, and lead to oppression and violence against innocent people. This problem has existed since time immemorial, even though there is no access to information throughout the world. Currently there are 2.5 trillion bytes of data and it increasing, leading to the next problem, i.e. faster at analyzing and identifying hoax news and real news. The ideal solution is using Deep Learning algorithm and the author chooses Recurrent Neural Network (RNN) method and it's particular method Long Short-Term Memory (LSTM). The accuracy obtained is 99%, greater than Machine Learning methods such as Rocchio or Multinomial Naive Bayes.

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Journal Info

Abbrev

bangkitindonesia

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

Description

Ruang lingkup Bangkit Indonesia adalah sebagai berikut : Domain Specific Frameworks and Applications IT Management dan IT Governance e-Government e-Healthcare, e-Learning, e-Manufacturing, e-Commerce ERP dan Supply Chain Management Business Process Management Smart Systems Smart City Smart Cloud ...