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Deteksi Kerusakan Jalan Menggunakan Pengolahan Citra Deep Learning di Kota Semarang

*Bandi Sasmito orcid scopus publons  -  Geodetic Engineering Departement - Faculty of Engineering, Diponegoro University, Semarang-Indonesia, Indonesia
Bagus Hario Setiadji  -  Departemen Teknik Sipil Fakultas Teknik, Universitas Diponegoro, Indonesia
Rizal Isnanto  -  Departemen Teknik Komputer Fakultas Teknik, Universitas Diponegoro, Indonesia
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Abstract
Jalan adalah kebutuhan krusial dalam aktivitas masyarakat. Jalan mempermudah akses transportasi dari tempat asal ke tujuan. Jalan juga penting sebagai infrastruktur transportasi darat untuk manusia dan barang. Namun, kondisi jalan yang tidak layak dapat menyebabkan kecelakaan. Pelacakan kondisi jalan sulit karena banyaknya jalan yang harus diperiksa. Penelitian ini menggunakan prinsip penginderaan jauh dengan teknologi Jaringan Syaraf Tiruan Deep Learning. YOLO (You Only Look Once) digunakan untuk deteksi kerusakan jalan. Hasil pendeteksian ditambahkan posisi atau lokasi dengan menggunakan Global Navigation Satellite System (GNSS), sehingga nantinya hasil deteksi dapat memberikan posisi atau lokasi yang akurat. Penelitian ini menghasilkan model identifikasi kerusakan jalan dengan nilai overall accuracy sebesar 88% dan nilai kappa accuracy sebesar 86% dan lokasi sebaran kerusakan yang memiliki koordinat posisi dengan akurasi RMSE sebesar ± 5,6 meter
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Keywords: jaringan syaraf tiruan; deep learning; penginderaan jauh; identifikasi kerusakan jalan; transportasi jalan; YOLO (You Only Look Once)

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