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DETEKSI AKSES JUDI ONLINE VIA TLS/SSL MENGGUNAKAN METODE RANDOM FOREST
This study aims to detect access to online gambling sites encrypted with TLS/SSL using machine learning-based network traffic fingerprint analysis, without accessing content to maintain privacy. The background focuses on the prevalence of illegal online gambling hidden behind encryption, which reduces the effectiveness of traditional methods such as DPI. The problem formulation includes the ide…
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- xiv, 103 hlm.; ilus.; tab.; 29 cm.
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- T1854602025
KOMPARASI DETEKSI ANOMALI LALU LINTAS JARINGAN PADA SITUS JUDI ONLINE MENGGUN…
This study discusses a comparison of the machine learning algorithms Random Forest and Decision Tree in detecting anomalies within network traffic on online gambling sites. The data was collected through network traffic capturing using Wireshark, followed by preprocessing stages that included data cleaning, encoding, balancing using Random Oversampling, and splitting into training and testing s…
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- xiv, 97 hlm.; ilus.; tab.; 29 cm.
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- T1854712025
IMPLEMENTASI DAN PERBANDINGAN PERFORMA YOLOV8, DAN STF-YOLO PADA SISTEM OBJEC…
Penelitian ini membahas implementasi dan perbandingan performa dua model deteksi objek berbasis deep learning, yaitu YOLOv8m dan STF-YOLOm (Swin Transformer Fusion YOLO). Tujuan penelitian ini adalah merancang model deteksi kendaraan menggunakan citra lalu lintas dari CCTV serta menganalisis performanya berdasarkan metrik evaluasi seperti precision, recall, dan mean Average Precision (mAP). Dat…
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- xiii, 79 hlm.; ilus.; tab.; 29 cm.
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- T1854542025
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