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All Journal Jurnal Pengabdian UntukMu NegeRI Juripol (Jurnal Institusi Politeknik Ganesha Medan) Jurnal SOLMA Jurnal Darma Agung Journal of Education Informatic Technology and Science Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Manajemen dan Bisnis JRMB (JURNAL RISET MANAJEMEN & BISNIS) JEKKP (JURNAL EKONOMI, KEUANGAN DAN KEBIJAKAN PUBLIK) Jurnal Administrasi Kantor Jurnal Manajemen Dan Akuntansi Medan Journal of Software Engineering and Information System (SEIS) Journal of Innovative and Creativity Sevaka: Hasil Kegiatan Layanan Masyarakat
Fauzan Azim
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Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Social Sciences Other

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Ablasi Kelompok Fitur Multi-View pada Random Forest untuk Deteksi Intrusi IIoT Amien, Januar Al; Anugrah Putra, Bayu; Azim, Fauzan; Medikawati Taufiq, Reny; Syahril, Syahril
JURNAL FASILKOM Vol. 16 No. 2 (2026): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v16i2.12438

Abstract

Internet of Things (IIoT) systems generate heterogeneous multisource telemetry data, including network traffic, host resource usage, and security logs. Intrusion detection studies commonly combine all available feature sources based on the assumption that incorporating more sources (multi-view) will always improve detection performance. This study examines this assumption using the X-IIoTID dataset through two experiments. First, feature selection based on Random Forest Gini importance was evaluated using five feature sizes (K = 10, 20, 30, 45, and 61), with cross-algorithm robustness assessed using Decision Tree, Logistic Regression, and K-Nearest Neighbors. Second, a systematic ablation study was conducted on seven combinations of three feature groups: Network (N), Host (H), and Log (L), with Timestamp excluded from the Network group to ensure consistent feature treatment. Using 299,999 samples, comprising 239,999 training and 60,000 test samples across 19 attack classes and a normal class, the results show that multiclass performance increased with the number of features, achieving an F1-macro of 0.876 at K = 10 and 0.912 at K = 61. The ablation study showed that the Full MultiView (N+H+L) achieved the best performance (F1-macro = 0.912), followed by N+H (0.905) and N+L (0.879). The Log group alone yielded low performance (0.098) but provided additional value when combined with Network features. These findings demonstrate that the effectiveness of multi-view intrusion detection depends on feature-source combinations rather than merely the number of sources, highlighting the importance of feature-group ablation in designing IIoT intrusion detection systems.
SYSTEMATIC LITERATURE REVIEW PERKEMBANGAN METODE COMPUTER VISION PADA PENGOLAHAN CITRA TAHUN 2017–2025 Akbar, Muhammad Arief; Azim, Fauzan
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 6 No. 2 (2026)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v6i2.11125

Abstract

The development of Computer Vision technology in recent years has shown significant growth along with advances in Deep Learning methods and the availability of large-scale datasets. Numerous studies have produced various approaches, architectures, and evaluation metrics, creating the need for a structured mapping to comprehensively understand the direction of this field. This study aims to analyze methodological trends, research task focuses, and dominant evaluation metrics in Computer Vision research. The method employed is a Systematic Literature Review (SLR) of 20 scientific article published between 2017 and 2025. The analysis process was conducted through data extraction covering method types, task focuses, datasets, and evaluation metrics used in each study. The results indicate that Convolutional Neural Networks and Vision Transformers are the most dominant architectures, with the primary research focuses on object detection, image classification, and video understanding. The most frequently used evaluation metrics are accuracy, mean Average Precision (mAP), and Intersection over Union (IoU). These findings reveal a gradual shift from convolution-based approaches toward transformer-based architectures that are more adaptive to large-scale visual data. This study provides a comprehensive overview of the development direction of Computer Vision and can serve as a reference for future research in selecting relevant methods and research focuses, both in terms of accuracy-oriented performance and computational efficiency.
Co-Authors Abadi, Abdi Nauli Abdul Rasyid M. S Adnan Arik, Muhammad Agusminarti Al Amien, Januar Amrani Andi Nova Bukit Anita Novialumi Anshari, Khairul Anugrah Putra, Bayu Aprilya, Regiesta Lintang Bayu Anugerah Putra Bayu Aruf Prabudi Dedy Dhamhudi Dian Wahyuningsih Donald Frensius Pasaribu Donald Frensius Pasaribu Eddi Suprayitno Effendi, Noverta Elviani, Sri Erinsyah Maulia Rangkuti Erinsyah Maulia Rangkuti Erinsyah Maulia Rangkuti Fadilal Hidayat, Ikhfal Fatma, Yulia Fitri Handayani Fitri Kartika Gunawan, Rahmad Hakim, Mursyalina Harun Mukhtar Ilham Hudi Aim Abdulkarim Kokom Komalasari, Ilham Hudi Aim Abdulkarim Ilmi Abdullah Ilmi Abdullah Ismail Nasution Kamo Waruru LINDA PUSPITASARI - A11111054, LINDA PUSPITASARI M Fiqri Manalu, Simon Patar Rizki Mualfah, Desti Muhammad Amirul Arif Muhammad Amirul Arif Muhammad Arief Akbar Muhammad Prasetyo Wibowo MUHAMMAD TAUFIK nabilla, nabilla putri Neng Sholihat Nur Augus Fahmi Nur M Ridha Tarigan Nuzuliati Nuzuliati Oki Harmiansyah Pakpahan, Evalina Putri Rahmawati Rahmad Firdaus Rahmarisa , Faty Rahmarisa, Faty Ramadhan, Rafi Fakhri Rismaja Putra Rizkina, Meiriza Safrida Saputra, M. Doni Sardiansyah Savita, Divani Sonata, Ilham Soni Soni, Soni Sri Wanti Nasution Supriadi Surya Sevi Wijayanna Syahril Syahril Taufiq, Reny Medikawati Tika Indria Tri Kartika Yudha Ulfa, Usni Yenny Lisbeth Siahaan Yenny Lisbeth Siahaan Yudha, Tri Kartika Yulia Nadila Yulia Rahman Zainal Zulkifli Siregar