Article Per Year (5 Year)
p-Index From 2021 - 2026
2.147
P-Index
This Author published in this journals
All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURIKOM (Jurnal Riset Komputer) Jurnal Karinov Journal of Innovation Information Technology and Application (JINITA) PELS (Procedia of Engineering and Life Science) Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Innovative Technologica: Methodical Research Journal Indonesian Journal of Applied Technology Journal of Electrical Engineering
Sukma Aji
Universitas Muhammadiyah Sidoarjo
Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Social Sciences Transportation

Published : 19 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

 1 
Hybrid CNN-LSTM for Indonesian Cyberbullying Detection on Social Media X Muhammad Hafizh Fattah; Rosid, Mochamad Alfan; Sukma Aji; Suprianto
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 2 (2026): Issues January 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i2.16938

Abstract

Cyberbullying on social media platform X has become a critical digital threat and requires automatic detection mechanisms to mitigate psychological impacts on victims. This study proposes a hybrid deep learning architecture that combines Convolutional Neural Network (CNN) for local feature extraction and Long Short-Term Memory (LSTM) for sequential context understanding in classifying Indonesian language cyberbullying comments. This study evaluates model performance using a dataset of 13,677 comments from social media X through a series of systematic testing scenarios, including the impact of regularization, utilization of FastText embeddings, and comparative studies against state-of-the-art models. Experimental results demonstrate that the Early Stopping mechanism is a critical factor in this architecture, where without this mechanism the model experiences accuracy degradation of up to 32%. The proposed CNN-LSTM model achieves 88.38% accuracy and 88.00% F1-Score, improving to 0.9559 AUC with FastText integration. This model achieves over 97% of IndoBERTweet's performance with 22 times lower computational complexity (4.97 million versus 110.88 million parameters) and outperforms machine learning methods such as SVM with an accuracy margin of more than 10 percentage points. This study concludes that the CNN-LSTM architecture offers a robust and efficient solution for cyberbullying detection, particularly for resource-constrained environments
Co-Authors Abdul Fadlil Abdul Fadlil Ade Eviyanti Andy Victor Pakpahan Arif Senja Fitrani Arif Wirawan Muhammad Arif Wirawan Muhammad Astutik, Ika Ratna Indra Davito Rasendriya Rizqullah Putra Davito Rasendriya Rizqullah Putra Eny Maryanti Fadlil , Abdul Fahmi Reza Ferdiansyah Faiz , Muhammad Nur Gautama Wijaya Haeruddin, . Hendra Winata Ika Ratna Indra Astutik Imam Riadi Imam Riadi Imam Riadi Imanudin, Giri Fajar Irwan Alnarus Kautsar Laura Sari Mochamad Alfan Rosid Mohammad Izzi Fajrin Muchlas, Muchlas Muhammad Hafizh Fattah Muhammad Nur Faiz Nur Faiz, Muhammad Nursapdahi, Nursapdahi Purwaningrum, Santi Putra F, M. Bagus Robby Gustian Santi Purwaningrum Sari, Laura Sarwenda Biduro Sunardi, Sunardi Suprianto Suprianto Suprianto Wahidiyah Kurniawati