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All Journal Jurnal Penelitian Komunikasi dan Opini Publik Sisforma: Journal of Information Systems Jurnal Ilmiah KOMPUTASI Jurnal Dimensi Pendidikan dan Pembelajaran JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jurnal Tekno Kompak Jurnal Pengabdian Masyarakat Teknik Jurnal Teknik Informatika (JUTIF) Brilliance: Research of Artificial Intelligence Jurnal Algoritma
Eka Angga Laksana
Universitas Widyatama
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Other

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TRAFFIC FLOW AND CONGESTION DETECTION WITH YOLOV8 AND BYTETRACK-BASED MULTI OBJECT TRACKING Fahrezi, Marchel Maulana; Laksana, Eka Angga
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2063

Abstract

The rapid urbanization witnessed in cities like Bandung, Indonesia, has emerged as a pressing issue, precipitating severe traffic congestion that poses challenges to economic growth and diminishes overall quality of life. This study endeavors to confront these multifaceted challenges through the development of a sophisticated real-time traffic surveillance and control system. The proposed system utilizes the current CCTV infrastructure in the city and incorporates advanced technologies like YOLOv8 for accurate vehicle detection and ByteTrack for dynamic real-time vehicle tracking. This system utilizes a comprehensive strategy, including multi-object tracking techniques to improve the precision of congestion detection. The system was thoroughly assessed in several places in Bandung, and it showed remarkable performance metrics. Specifically, YOLOv8 achieved an impressive 80% accuracy rate in vehicle detection, showcasing its efficacy in discerning vehicles within complex urban environments. Simultaneously, ByteTrack exhibited an average error rate of 17% in vehicle counting, further Strengthening the system's capabilities in accurately quantifying vehicular traffic. Furthermore, the combination of YOLOv8 and ByteTrack in a multi-object tracking paradigm yielded an 80% accuracy rate in congestion detection, emphasizing the system's robustness in real-time traffic management scenarios. These findings underscore the immense potential of the integrated YOLOv8 and ByteTrack system in traffic management strategies and alleviating congestion in smart cities like Bandung. This research has produced precise outcomes in identifying and quantifying the traffic congestion in various scenarios.
Rancang Bangun Teknologi Edukasi Berbasis Moodle dan Private Cloud di SMAN 26 Bandung Nafysah, Mutiara; Laksana, Eka Angga
JURNAL DIMENSI PENDIDIKAN DAN PEMBELAJARAN Vol 11 No 2 (2023): July 2023
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/dpp.v11i2.7151

Abstract

Teknologi informasi dan komunikasi berkembang dengan pesat dan telah menyentuh banyak bidang dalam membantu pekerjaan manusia. Salah satu bidang yang telah disentuh oleh teknologi informasi dan komunikasi adalah bidang pendidikan dengan penggunaan tekonologi e-learning dalam membantu kegiatan belajar mengajar. E-learning digunakan oleh banyak sekolah maupun universitas dalam melaksanakan kegiatan belajar mengajar terutama di masa pandemi. Meskipun sekarang kebanyakan kegiatan belajar mengajar telah dilakukan secara offline, website e-learning masih bisa digunakan untuk melaksanakan ujian maupun ulangan harian. Moodle adalah salah satu framework LMS (Learning Management System) open-source yang dapat diperoleh secara gratis dengan portal e-learning yang bisa dimodifikasi agar dapat disesuaikan sebagaimana kebutuhan penggunanya. Moodle yang telah dimodifikasi tentu baru dapat digunakan jika sudah diisi dengan data-data tertentu mulai dari pengguna aplikasi sampai pembagian kelas dan mata pelajaran. Setelah data primer didapat, data tersebut perlu diolah terlebih dahulu sesuai format sistem sebelum bisa di input ke dalam Moodle.
Co-Authors -, Sunjana Adrian, Mochammad Ilham Ardhian Ekawijana Ase Suryana Azizah Zakiah Benny Yustim Fahrezi, Marchel Maulana Heri Heryono Herlistiono, Iwa Ovyawan Madsu, Yosi Malatta Mahendra, Randa Maulana, Rafli Iqbal Nafysah, Mutiara Sukenda . Viddi Mardiansyah