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PEMANTAUAN POLA PERILAKU LALU LINTAS BERBASIS JARINGAN CCTV BERDASARKAN TEKNOLOGI ANALISIS DATA MENGGUNAKAN YOLOV8 DENGAN ALGORITMA HIERARCHICAL CLUSTERING

This study presents the design of a traffic behavior monitoring system based on CCTV networks by comparing two algorithmic approaches: YOLOv8 for real-time object detection and Hierarchical Clustering for unsupervised object grouping without prior labeling. The system is developed to automatically identify behavioral patterns in traffic, such as violations involving riders not wearing helmets. Image and video data were collected from several strategic locations in Palembang and processed through stages of annotation, model training, and performance evaluation. The YOLOv8 model demonstrated high accuracy based on evaluation metrics including confusion matrix, precision, recall, and F1-score. Meanwhile, the Hierarchical Clustering results were visualized through dendrograms, serving as a comparative reference to the YOLOv8-based classification. The findings indicate that integrating both supervised and unsupervised methods offers complementary insights and can serve as a foundation for developing more robust, data-driven traffic surveillance systems.

Availability
#
Central Library (REFERENS) T1818442025
T181844
Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1818442025
Publisher
Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya.,
Collation
xiv, 101 hlm.; ilus.; tab, 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
003.307
Content Type
Text
Media Type
unmediated
Carrier Type
other (computer)
Edition
-
Subject(s)
Model dan simulasi komputer
Prodi Sistem Komputer
Specific Detail Info
-
Statement of Responsibility
Other version/related
TitleEditionLanguage
IMPLEMENTASI HUMAN-MACHINE INTERACTION PADA SERVICE ROBOT BERBASIS INTEGRASI PERSEPSI DAN NAVIGASI-id
PENGEMBANGAN SISTEM SORTIR OTOMATIS BUAH MENGGUNAKAN MODEL YOLOV8id
ANALISIS SENTIMEN TERHADAP KEMACETAN LALU LINTAS MENGGUNAKAN YOLOV8 DENGAN ALGORITMA RECURRENT NEURAL NETWORK (RNN) BERDASARKAN DATA PADA SOSIAL MEDIA DAN REKAMAN CCTV DI JALAN PROTOKOL PALEMBANGid
DETEKSI PELANGGARAN KENDARAAN MELAWAN ARUS LALU LINTAS DI JALAN KOTA PALEMBANG MENGGUNAKAN YOLOV8 DAN METODE RANDOM FOREST UNTUK MENGUKUR TINGKAT PELANGGARANid
PENINGKATAN KINERJA SISTEM DETEKSI BATU GINJAL PADA CITRA CT SCAN MENGGUNAKAN ALGORITMA YOLOv8 DENGAN MODIFIKASI BACKBONE LAYER-id
PENGEMBANGAN SISTEM SORTIR OTOMATIS BUAH MENGGUNAKAN MODEL YOLOV8id
ANALISIS SENTIMEN TERHADAP KEMACETAN LALU LINTAS MENGGUNAKAN YOLOv8 DENGAN ALGORITMA GATED RECURRENT UNIT BERDASARKAN DATA PADA SOSIAL MEDIA DAN REKAMAN VIDEO DI JALAN PROTOKOL PALEMBANGid
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