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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JSI (Jurnal sistem Informasi) Universitas Suryadarma Jurnal Mantik Tematik : Jurnal Teknologi Informasi Komunikasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Kajian Ilmiah Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat IICS Journal of Students‘ Research in Computer Science (JSRCS) Jurnal Abdimas Ekonomi Dan Bisnis (JAMEB) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Jurnal Sistim Informasi dan Teknologi Jurnal Pengabdian Pelitabangsa International Journal of Information Technology and Computer Science Applications (IJITCSA) Jurnal Sistem Informasi Indonesian Journal of Education And Computer Science Jurnal Inovasi dan Pengembangan Hasil Pengabdian Masyarakat VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Journal of Computer Science Contributions (Jucosco) The Indonesian Journal of Computer Science Journal of Informatics and Information Security Jurnal Komtika (Komputasi dan Informatika)
Priatna , Wowon
Informatika, Fakultas Ilmu Komputer, Universitas Bhayangkara Jakarta Raya
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Network Intrusion Detection Using Transformer Models and Natural Language Processing for Enhanced Web Application Attack Detection Wowon Priatna; Irwan Sembiring; Adi Setiawan; Iwan Setyawan
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 13 No. 3 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i3.82462

Abstract

The increasing frequency and complexity of web application attacks viralslot necessitate more advanced detection methods. This research explores integrating Transformer models and Natural Language Processing (NLP) techniques to enhance network intrusion detection systems (NIDS) viralslot. Traditional NIDS often rely on predefined signatures and rules, limiting their effectiveness against new attacks. By leveraging the Transformer's ability to capture long-term dependencies and the contextual richness of NLP, this study aims to develop a more adaptive and intelligent intrusion detection framework. Utilizing the CSIC 2010 dataset, comprehensive preprocessing steps such as tokenization, stemming, lemmatization, and normalization were applied. Techniques like Word2Vec, BERT, and TF-IDF were used for text representation, followed by the application of the Transformer architecture. Performance evaluation using accuracy, precision, recall, F1 score, and AUC demonstrated the superiority of the Transformer-NLP model over traditional machine learning methods. Statistical validation through Friedman and T-tests confirmed the model's robustness and practical significance. Despite promising results, limitations include the dataset's scope, computational complexity, and the need for further research to generalize the model to other types of network attacks. This study indicates significant improvements in detecting complex web application attacks viralslot, reducing false positives, and enhancing overall security, making it a viable solution for addressing increasingly sophisticated cybersecurity threats
Deteksi Stunting Menggunakan Dual-Vae, Gan, Dan Transformer Pada Data Antropometri Wowon Priatna; Joni Warta; Agus Hidayat; Adam Arif Budiman
Jurnal Kajian Ilmiah Vol. 26 No. 3 (2026): September 2026
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/g4x45463

Abstract

Stunting detection based on anthropometric data requires a classification model capable of capturing complex relationships among child growth characteristics. This study developed a stunting detection model integrating Dual Variational Autoencoder (Dual-VAE), Generative Adversarial Network (GAN), and Transformer using age, sex, weight, and height as predictors. The dataset consisted of 40,071 records of children aged 0–59 months from Jeneponto Regency, Indonesia. Two class-oriented VAE branches were used to learn complementary latent representations of stunted and non-stunted children. GAN-based enrichment was applied to the stunted latent representation, while the Transformer modeled interactions among the resulting latent features. Model performance was evaluated using stratified five-fold cross-validation. The proposed model achieved an accuracy of 0.9960 ± 0.0007, F1-score of 0.9950 ± 0.0008, G-Mean of 0.9957 ± 0.0007, MCC of 0.9917 ± 0.0014, AUROC of 0.9999 ± 0.0001, and AUPRC of 0.9998 ± 0.0001. The results showed that combining class-oriented latent representations, controlled generative enrichment, and feature-interaction modeling produced high and consistent classification performance for anthropometric-based stunting detection.
Co-Authors -, Rasim Adam Arif Budiman Ade Iriani Adi Setiawan Agung Nugroho Agung Nugroho Agus Hidayat Agus Hidayat Agus Hidayat Agus Hidayat Aida Fitriyani, Aida Ajif Yunizar Pratama Yusuf Alexander, Allan D Alhillah, Yumaris Alfi Andi Lawrence Hutahaean, Johanes Andi Rahman Andri Fajriya Anisya Wulandari Annisa Oktavianti Hermadi Aprilyana, Dhea Putri Asep R. Hamdani Asep Ramdhani M Asep Ramdhani Mahbub Asep Ramdhani Mahbub Atika , Prima Dina Danny Manongga Dimas Abimanyu Prasetyo Dwi Budi Srisulistiowati Dwipa Handayani Dzulqiyana, Afina Putri Eka Nur A’ini Endah Prawesti Ningrum Endang Retnoningsih Enggar Putera, dkk, Diaz Evi Maria Fadjriya, Andry Faisal Adi Saputra Fajar Mukharom Fathurrazi, Ahmad Febry Sandrian Sagala Fefbiansyah Hasibuan Galih Apriansha Pradana Hadi Kusmara Hamdani, Asep R. Hendarman Lubis Hendharsetiawan, Andy Achmad Herlawati Herlawati Hernowo, Pandit Hindriyanto Dwi Purnomo Ikhsan Romli Ilham Rizky Widianto Irwan Sembiring Ismaniah Ismaniah Ismaniah, Ismaniah Iwan Setyawan Joni Warta Joni Warta Joni Warta Joniwarta Joniwarta Jumi Saroh Hidayat Kapriadi, Engkap Karyaningsih, Dentik Khoirunnisaa, Nabiilah Kustanto , Prio Lestari, Tyastuti Sri Manrejo, Sumarno Mayadi Mayadi Meutia, Kardinah Indrianna Mugiarso Mugiarso, Mugiarso Muhammad Khaerudin Muhammad Yasir Noe’man,, Achmad Nurjeli Nurjeli Nursal, M. Fadhli Pasaribu, Ahmad Muchlisin Natas Pradana , Galih Apriansha Prima Dina Atika Purnomo, Rakhmat Purnomo, Rakhmat Rahmadanti, Regita Ari Rahmadya Trias Handayanto Rakhmat Purnomo Rasim Rasim Rasim . Rasim Rasim Rejeki , Sri Rinaldi Tunnisia Ritzkal, Ritzkal Sagala, Febry Sandrian Saputra , Faisal Adi Silvi - Siti Setiawati SITI SETIAWATI Siti Setiawati Siti Setiawati, Andika Yusuf Hidayat Sri Lestari, Tyastuti Sri Rejeki Sri Yulianto Joko Prasetyo Sudiantini, Dian Sulistiyo, Dwi Suryadi Sutarto Wijono Syahbaniar Rofiah Tb Ai Munandar, Tb Ai Theophilus Wellem Tia Aulia Tri Dharma Putra Tri Dharma Putra Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Tyastuti Sri Lestari Wiyanto Wiyanto