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All Journal Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komtika (Komputasi dan Informatika) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) IJIIS: International Journal of Informatics and Information Systems Journal of Computer System and Informatics (JoSYC) KLIK: Kajian Ilmiah Informatika dan Komputer Prosiding Seminar Nasional Program Pengabdian Masyarakat Techno Prosiding University Research Colloquium Borobudur Informatics Review IJESPG (International Journal of Engineering, Economic, Social Politic and Government) journal Jurnal Komtika (Komputasi dan Informatika)
Mukhtar Hanafi
Universitas Muhammadiyah Magelang, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Social Sciences

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Traffic Congestion Detection Using YOLOv8 Algorithm With CCTV Data Indra Bayu Pangestu; Maimunah Maimunah; Mukhtar Hanafi
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9953

Abstract

Community development and growth according to data from the Central Java Statistics Agency regarding the number of vehicles in Central Java Province in 2021 is 20 320 743. The increasing growth of society has caused vehicle density which is a serious problem in urban areas. This study developed a congestion detection system using the YOLOv8 algorithm to analyze traffic density from CCTV footage. Automated detection of traffic congestion is a critical challenge in urban transport management. YOLOv8, a fast and accurate object detection algorithm, is used to identify vehicles and count their number in various areas of the highway. This information is then processed to assess road congestion conditions, with the aim of detecting congestion. The data obtained were tested on two road scenarios and traffic conditions to evaluate the performance of the system. The results showed that the proposed system was able to detect congestion with an accuracy level of 59.2% from several experiments. The use of YOLOv8 enables real-time detection with efficient computing resources, making it a potential solution for large-scale deployment. This research shows that the incorporation of advanced object detection algorithms such as YOLOv8 with CCTV data can provide an effective solution for traffic management in large cities. This system is expected to improve response to congestion, help control traffic, and reduce the negative impact of congestion in urban areas
Co-Authors Achmat Mujafar Ajeng Tri Rahayu Alfathin, Abdullah Husain Alfathin, Abdullah Husain Alif Kemal Verdito Andi Widiyanto Andi Widiyanto Ardhin Primadewi Arief Setyawan Asroni Asroni Asti Nur Imani Auliya Burhanuddin Bambang Pujiarto Bambang Pujiarto Bambang Pujiarto Cahya Damarjati Choirul Anam AM Diponegoro Dewantara, Helmy Dewantara, Helmy Dimas Sasongko Eky Rizky Prasetya Emilya Ully Artha Endah Ratna Arumi Hafidz Fahrizal Rahman Haka, Qosim Nurdin Hariyanto, Yenik Heri Purwanto Humaid Husain As’ad Indra Bayu Pangestu Layli Nur'Aini Maimunah Maimunah Maimunah Meidar Hadi Avizenna Mohammad Rahardian Adhitama Mubarak, Rosyid Muhammad Alfadha Termahadi Muhammad Hafizh Hamdanuddinsyah Nugraha, Setiya Nugraha, Setiya Nugroho Agung Prabowo Nugroho Agung, Nugroho Nurhidayat, Linggarjati Rudyan Nurhidayat, Linggarjati Rudyan Nuryanto Nuryanto Nuryanto Prasetyo, Ahmad Zudha Prasetyo, Ahmad Zudha Purwono Hendradi Qosim Nurdin Haka R Arri Widyanto Ramadhan, Radzi Diva Rochanah, Rochanah Rusdjijati, Retno Sidik Priyo Utomo Sukmasetya, Pristi Sunarni Sunarni Suta, Saka Nano Utomo, Sidik Priyo Vyan Martha, Aldo Wildan Fatkhul Barry