Article Per Year (5 Year)
p-Index From 2020 - 2025
2.422
P-Index
This Author published in this journals
All Journal TEKNIK INFORMATIKA Syntax Jurnal Informatika CESS (Journal of Computer Engineering, System and Science) Jurnal Informatika Indonesian Journal of Artificial Intelligence and Data Mining Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Informatika Universitas Pamulang Jurnal Nasional Komputasi dan Teknologi Informasi JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of Applied Engineering and Technological Science (JAETS) Jurnal Tekinkom (Teknik Informasi dan Komputer) JUKI : Jurnal Komputer dan Informatika Jurnal Computer Science and Information Technology (CoSciTech)
Fadhilah Syafria
Universitas Islam Negeri Sultan Syarif Kasim Riau
Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Neuroscience Transportation

Published : 18 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Computer Science and Information Technology (CoSciTech)

 1 
Klasifikasi Clickbait Menggunakan Transformers Mori Hovipah Mori Hovipah; Elin Hearani; Jasril Jasril; Fadhilah Syafria
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4713

Abstract

Clickbait is a news title created by the author with the aim of attracting the getting to get readers so they Never miss a headline. Clickbait headlines are typically quirky, confusing, and use exaggerated sentences to entice readers to click on links. However, clickbait headlines that look very attractive often do not match the information in the headlines and the content of the news, which can lead to the spread of fake news and hoaxes. Then classification of clickbait news titles is carried out, for this research, clickbait classification was carried out for news titles will be carried out using the Transformers method. The number of news titles used in this study amounted to 6632 news titles. The process of classification of news titles in this study includes: collecting data, labeling data, preprocessing, EDA, and classification using transformers. The best accuracy value obtained in this study was 63% for precision of 0.63 and recall of 1 using a data division of 10%: 90%.
Co-Authors Abdussalam Al Masykur Agung Syaiful Rahman Ahmad Paisal Alwis Nazir Ariq At-Thariq Putra Benny Sukma Negara Deny Ardianto Devi Julisca Sari Dina Septiawati Eka Pandu Cynthia Elin Haerani Elin Hearani Elvia Budianita Febi Yanto Felian Nabila Fitra Lestari Iis Afrianty Ismail Marzuki Ismar Puadi Iwan Iskandar Jasril Jasril Karina Julita Lestari Handayani Lola Oktavia Mori Hovipah Mori Hovipah Morina Lisa Pura Nazruddin Safaat H Novriyanto Novriyanto Puspa Melani Almahmuda Rahmad Kurniawan Reski Mai Candra Riska Yuliana Said Nanda Saputra Silfia Silfia Siska Kurnia Gusti Suwanto Sanjaya Yusra, Yusra