Fake News (Hoaxes) Detection on  Twitter Social Media Content through Convolutional Neural Network (CNN) Method

Fauzaan Rakan Tama; Yuliant  Sibaroni

doi:10.35877/454RI.jinav1525

Fauzaan Rakan Tama Telkom Unversity (ID)
Yuliant Sibaroni Telkom Unversity (ID)

https://doi.org/10.35877/454RI.jinav1525

Keywords: social media, hoax, Twitter, convolutional neural network, tf-idf, tf-rf

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Abstract

The use of social media is very influential for the community. Users can easily post various activities in the form of text, photos, and videos in social media. Information on social media contains fake news and hoaxes that will have an impact on society. One of the most social media used is Twitter. This study aims to detect fake news found on the Tweets using the Convolutional Neural Network (CNN) method by comparing the weighting features used of the Term Frequency Inverse Document Frequency (TF-IDF) and the Term Frequency-Relevance Frequency (TF-RF). The highest accuracy was obtained in the Term Frequency-Relevance Frequency (TF-RF) weighting feature with an accuracy of 84.11%, while in the Term Frequency Inverse Document Frequency (TF-IDF) weighting feature with an accuracy of 80.29%.

References

Batoebara, M. U., Suyani, E., & Nuraflah, C. A. (2020a). Literasi Media dalam Menanggulangi Berita Hoaks ( Studi Pada Siswa SMKN 5 Medan ). Jurnal Warta Edisi 63, 14, 34–41. http://jurnal.dharmawangsa.ac.id/index.php/juwarta/article/download/541/530

Batoebara, M. U., Suyani, E., & Nuraflah, C. A. (2020b). Literasi Media dalam Menanggulangi Berita Hoaks ( Studi Pada Siswa SMKN 5 Medan ). Jurnal Warta Edisi 63, 14(1), 34–41.

Dirjen, S. K., Riset, P., Pengembangan, D., Dikti, R., Wintang Kencana, C., Budi, E., #2, S., & Kurniawan, I. (2017). Terakreditasi SINTA Peringkat 2 Hoax Detection on Twitter using Feed-forward and Back-propagation Neural Networks Method. Masa Berlaku Mulai, 1(3), 648–654.

Eka Sembodo, J., Budi Setiawan, E., & Abdurahman Baizal, Z. (2016). Data Crawling Otomatis pada Twitter. October 2018, 11–16. https://doi.org/10.21108/indosc.2016.111

Farid, H. K., Setiawan, E. B., & Kurniawan, I. (2020a). Implementation Information Gain Feature Selection for Hoax News Detection on Twitter using Convolutional Neural Network (CNN). Indonesia Journal on Computing (Indo-JC), 5(3), 23–36. https://doi.org/10.34818/INDOJC.2020.5.3.506

Farid, H. K., Setiawan, E. B., & Kurniawan, I. (2020b). Implementation Information Gain Feature Selection for Hoax News Detection on Twitter using Convolutional Neural Network (CNN). Indonesia Journal on Computing (Indo-JC), 5(3), 23–36. https://doi.org/10.34818/INDOJC.2020.5.3.506

Istiani, N., & Islamy, A. (2020). Fikih Media Sosial Di Indonesia. Asy Syar’Iyyah: Jurnal Ilmu Syari’Ah Dan Perbankan Islam, 5(2), 202–225. https://doi.org/10.32923/asy.v5i2.1586

Kurniawan, A. A., & Mustikasari, M. (2021). Implementasi Deep Learning Menggunakan Metode CNN dan LSTM untuk Menentukan Berita Palsu dalam Bahasa Indonesia. Jurnal Informatika Universitas Pamulang, 5(4), 544. https://doi.org/10.32493/informatika.v5i4.6760

Lan, M., Tan, C. L., & Low, H. B. (2006). Proposing a new term weighting scheme for text categorization. Proceedings of the National Conference on Artificial Intelligence, 1, 763–768.

MacLaughlin, H., & Greenwood, S. (2010). Weight management of obese patients on the renal ward. Journal of Renal Nursing, 2(3), 116–121. https://doi.org/10.12968/jorn.2010.2.3.48079

Parewe, A. M. A. K., Aman, A., & Dewang, D. P. M. (2021a). Perbandingan Algoritma Winnowing dan Algoritma Manber dalam Mendeteksi Berita Hoax di Media Sosial. Seminar Nasional Teknologi Informasi Dan Komputer, 41–46.

Parewe, A. M. A. K., Aman, A., & Dewang, D. P. M. (2021b). Perbandingan Algoritma Winnowing dan Algoritma Manber dalam Mendeteksi Berita Hoax di Media Sosial. Seminar Nasional Teknologi Informasi Dan Komputer, 41–46.

Shafirra, N. A., & Irhamah, I. (2020). Klasifikasi Sentimen Ulasan Film Indonesia dengan Konversi Speech-to-Text (STT) Menggunakan Metode Convolutional Neural Network (CNN). Jurnal Sains Dan Seni ITS, 9(1). https://doi.org/10.12962/j23373520.v9i1.51825

Sriyano, C. S., & Setiawan, E. B. (2021). Pendeteksian Berita Hoax Menggunakan Naive Bayes Multinomial Pada Twitter dengan Fitur Pembobotan TF-IDF. E-Proceeding of Engineering : Vol.8, No.2, 8(2), 3396–3405.

Yoviananda, C., & Fahrudin, T. M. (2022). Implementation of Deep Learning to Detect Indonesian Hoax News with Convolutional Neural Network Method. IJEEIT International Journal of Electrical Engineering and Information Technology, 4(2), 86–93. https://doi.org/10.29138/ijeeit.v4i2.1525

Yunanto, R., Purfini, A. P., & Prabuwisesa, A. (2021). Survei Literatur: Deteksi Berita Palsu Menggunakan Pendekatan Deep Learning. Jurnal Manajemen Informatika (JAMIKA), 11(2), 118–130. https://doi.org/10.34010/jamika.v11i2.5362