Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Dwi Andhara Valkyrie
Unknown Affiliation
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Language Processing for Detecting Fake News on Twitter Using a Long Short-Term Memory Architecture Rini Sovia; Dwi Andhara Valkyrie; Ruri Hartika Zain; Firdaus
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6570

Abstract

The rapid spread of misinformation on social media platforms, particularly X (formerly Twitter), poses a significant challenge to public trust and democratic integrity. Fake news is often crafted to deceive readers and manipulate public opinion, especially in political contexts such as the 2024 Regional Head Elections (Pilkada 2024). Although various measures have been proposed to mitigate this issue, achieving an effective balance between controlling misinformation and preserving free speech remains a challenge. This study aims to address this problem by developing a fake news detection model based on Natural Language Processing (NLP) and Long Short-Term Memory (LSTM). The dataset used in this study was collected from public tweets related to Pilkada, with Kompas.com serving as the validation source to verify content authenticity. Experimental results show that the proposed LSTM model outperformed traditional classification methods, achieving a precision, recall, and F1-score of 0.95, along with an overall accuracy of 94.90%. Confusion matrix analysis further confirmed the reliability of the model by demonstrating low misclassification rates. This study contributes to the advancement of AI-driven hoax detection systems, offering an automated and scalable solution for combating misinformation in political discourse.
Co-Authors Firdaus Rini Sovia Ruri Hartika Zain