Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2021
Deteksi Berita Palsu Menggunakan CNN-RNN dalam Penentuan Penyebaran Berita
Dublin Core
Title
Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2021
Deteksi Berita Palsu Menggunakan CNN-RNN dalam Penentuan Penyebaran Berita
Deteksi Berita Palsu Menggunakan CNN-RNN dalam Penentuan Penyebaran Berita
Subject
Data Mining, CNN-RNN, Berita Palsu, Media Sosial
Data Mining, CNN-RNN, Fake News, Social Media
Data Mining, CNN-RNN, Fake News, Social Media
Description
Berkembangnya zaman maka berkembang juga teknologi yang ada, didalam teknologi terdapat adanya komunikasi yang melibatkan beberapa orang melalui media sosial online. Media sosial saat ini tidak hanya dapat digunakan untuk berkomunikasi, tetapi juga untuk menyebarkan berita, dan sebagainya, dalam media sosial ini tentu saja tidak semua orang berniat baik, ada juga yang berniat jahat dengan cara menyebarkan berita palsu. Beberapa orang yang membaca suatu berita tidak memeriksa silang referensi dari sumber berita yang ada dan memastikan kredibilitas berita. Oleh karena itu, dengan mempertimbangkan skala pengguna dan kontributor media sosial, diperlukan adanya deteksi berita palsu ini yang memungkinkan untuk mengambil tindakan perbaikan, serta dapat memfilter mana berita benar dan berita palsu. Dalam beberapa penelitian sebelumnya belum terdapat penggolongan berdasarkan sumber dan tahun berita, topik dari data yang ada, cara pencegahan penyebaran berita palsu dan mengkonfirmasi keaslian akun berita. Dalam penelitian ini bertujuan untuk menggolongkan berita menurut sumber dan tahun berita, klasifikasi berdasarkan topik, pencegahan, dan deteksi akun dari berita palsu. Dalam penelitian ini akan menggunakan metode CNN-RNN yang dimana metode tersebut diharapkan dapat menyempurnakan penelitian sebelumnya. Hasil penelitian ini yaitu menghasilkan akurasi menggunakan CNN-RNN dalam penentuan penyebaran berita sebesar 50.1244 % dan 52.9851 %
With the development of the times, the existing technology also develops, in technology there is communication that involves several people through online social media. Today's social media can not only be used to communicate, but also to spread news, and so on, in this social media of course not everyone has good intentions, there are also those who have bad intentions by spreading fake news. Some people who read a story do not cross-check the references from existing news sources and ensure the credibility of the news. Therefore, taking into account the scale of social media users and contributors, it is necessary to have this fake news detection that allows for corrective action, and can filter out which news is true and fake news. In some previous studies, there has been no classification based on the source and year of news, topics from existing data, ways to prevent the spread of fake news and confirm the authenticity of news accounts. This study aims to classify news by source and year of news, classification by topic, prevention, and account detection of fake news. In this study, the CNN-RNN method will be used which is expected to be able to complete previous research. These aspects such as source, year, topic, and prevention of fake news contribute to improving which methods are most suitable for detecting fake news on social media.
With the development of the times, the existing technology also develops, in technology there is communication that involves several people through online social media. Today's social media can not only be used to communicate, but also to spread news, and so on, in this social media of course not everyone has good intentions, there are also those who have bad intentions by spreading fake news. Some people who read a story do not cross-check the references from existing news sources and ensure the credibility of the news. Therefore, taking into account the scale of social media users and contributors, it is necessary to have this fake news detection that allows for corrective action, and can filter out which news is true and fake news. In some previous studies, there has been no classification based on the source and year of news, topics from existing data, ways to prevent the spread of fake news and confirm the authenticity of news accounts. This study aims to classify news by source and year of news, classification by topic, prevention, and account detection of fake news. In this study, the CNN-RNN method will be used which is expected to be able to complete previous research. These aspects such as source, year, topic, and prevention of fake news contribute to improving which methods are most suitable for detecting fake news on social media.
Creator
Khoirinisa Umi Rahmawati
Publisher
Universitas Semarang
Date
13 Oktober 2021
Contributor
Sri Wahyuni
Rights
ISSN: 2614-1205
Format
PDF
Language
Indonesian
Type
Text
Coverage
Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2021
Files
Citation
Khoirinisa Umi Rahmawati, “Prosiding Seminar Nasional Ilmu Komputer Universitas Semarang 2021
Deteksi Berita Palsu Menggunakan CNN-RNN dalam Penentuan Penyebaran Berita,” Repository Horizon University Indonesia, accessed April 11, 2025, https://repository.horizon.ac.id/items/show/3497.
Deteksi Berita Palsu Menggunakan CNN-RNN dalam Penentuan Penyebaran Berita,” Repository Horizon University Indonesia, accessed April 11, 2025, https://repository.horizon.ac.id/items/show/3497.