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All Journal Teika Infotech Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) IJIS - Indonesian Journal On Information System Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Ilmiah Media Sisfo JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Tekinkom (Teknik Informasi dan Komputer) BERNAS: Jurnal Pengabdian Kepada Masyarakat Journal of Advanced in Information and Industrial Technology (JAIIT) Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) Jurnal Mandala Pengabdian Masyarakat Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Bulletin of Information Technology (BIT) Batara Wisnu : Indonesian Journal of Community Services PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Buletin Ilmiah Informatika Teknologi JAMU : Jurnal Abdi Masyarakat UMUS Innovative: Journal Of Social Science Research Jurnal Ilmiah Sistem Informasi Software Development Digital Business Intelligence and Computer Engineering Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Pustabiblia: Journal of Library and Information Science
Mochammad Darip
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Journal : bulletin of information technology bit

 1 
Implementasi Support Vector Machine (SVM) Untuk Deteksi Serangan Jaringan Pada Sistem Keamanan Jaringan Kampus Darip, Mochammad; Sapaatullah, Asep; Rahmat, Rahmat
Bulletin of Information Technology (BIT) Vol 7 No 1: Maret 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i1.2602

Abstract

Network security in campus environments faces increasingly complex challenges due to the rapid growth of internet usage, digital academic systems, and the large number of devices connected to the network. One of the main problems is the limitation of conventional security systems in detecting new or anomalous network attacks. Traditional systems generally rely on predefined attack signatures, making them ineffective against previously unknown attacks. Therefore, this study proposes a solution by implementing the Support Vector Machine (SVM) method for automatic network attack detection. The research method includes the collection of campus network traffic data, data preprocessing stages such as data cleaning, normalization, and feature selection, SVM model training, and performance evaluation using confusion matrix and ROC curve. The results show that the SVM model is able to classify normal traffic and attack traffic with very high accuracy. These findings indicate that SVM is an effective method for intrusion detection and can significantly enhance campus network security in an adaptive and efficient manner.
Analisis Performa Support Vector Machine untuk Klasifikasi Risiko Kredit Nasabah pada Perbankan Daerah Sapaatullah, Asep; Rahmat, Rahmat; Darip, Mochammad
Bulletin of Information Technology (BIT) Vol 7 No 1: Maret 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i1.2603

Abstract

Credit risk assessment is a crucial component of the banking system because it directly relates to a financial institution's ability to manage potential losses due to non-performing loans. Banks often face difficulties in accurately classifying customer credit risk levels, especially when the data being analyzed is complex, nonlinear, and contains interacting variables. Conventional methods such as regression analysis often fail to capture hidden patterns in such data. Therefore, this study aims to apply the Support Vector Machine (SVM) algorithm as a solution to classify bank customers' credit risk levels based on attributes such as income, loan amount, length of employment, payment history, debt-to-income ratio, and asset ownership status. The research process begins with data collection and pre-processing, including data cleaning and normalization to ensure a uniform distribution of values. The data is then divided into training and test data with specific proportions. An SVM model is then applied using several kernel types, such as linear, polynomial, and radial basis function (RBF), to determine the best-performing kernel. Model evaluation is performed using accuracy, precision, recall, and F1-score metrics to measure classification performance. Test results show that the SVM model with the RBF kernel provided the best results, achieving an accuracy rate of over 90% and minimizing classification errors in the high-risk category. In conclusion, the application of the SVM algorithm has proven effective in classifying customer credit risk levels with high accuracy and stability, making it a reliable tool for banks in the creditworthiness analysis process and more accurate, data-driven strategic decision-making
Co-Authors Abdul Halim Ali Rochman Ali Rohman Ali Rohman Anam, Aan Khoirul Anugerah Agung Auliana, Sigit Aziz, Aflahul Basuki Rakhim Setya Permana Eris Purnama Gelard Untitha Pratama Gerald Untirtha Pratama Hamdan Hamdan Hamdan Hasan Siddiq Heru Maulana, Yozie Iis Nurasiah Irvan Septiandi Makin, Samsul Malik Farid Hanafi Maman Maman Masyhuri Masyhuri, Maman Maulana, Rafli MMSI Irfan ,S. Kom Muhamad Hidayatullah Muhamad Shiraj Al-Ayyubi Nana Supiana Nova Fitriyani Novita Sari Nurul Khoer Hidayah, Nadaa Parimin Pratama, M. Arieza Purnama, Eris Rahmat Rahmat Rizki, Wahyu Roy, Sujan Chandra Rudianto Rudianto Sapaatullah, Asep Saputro, Ahmad Dwi Sayyidah, Arnaeta Aprilia Siti Bunga Cinta Sunardi Sunardi Sunardi Sunardi Supiana, Nana Ubaedilah, Ikbal Wahyu Amaldi Yansyah, Mardi