Optimasi Mendeteksi Klasifikasi Citra Digital Logo Mobil Indonesia Dengan Metode Single Shot Multibox Detector

Dadang Iskandar Mulyana, Muhammad Zikri

Abstract


Logo kendaraan mobil merupakan salah satu fitur yang dapat mengidentifikasi suatu kendaraan. Namun, banyak dari sistem transportasi cerdas yang saat ini masih dalam pengembangan dan belum menggunakan sistem pengenalan logo kendaraan mobil sebagai bagian dari alat identifikasi kendaraan. Metode sebelumnya yaitu dengan Metode Local Binary Pattern dan Random Forest memiliki tingkat pengenalan yang rendah untuk sebagian besar logo kendaraan kecil dan kinerja yang buruk di bawah lingkungan yang rumit. Tujuanya pada penelitian ini untuk mengenalkan logo mobil yang unik serta untuk meningkatkan akurasi deteksi pada logo mobil di Indonesia. Logo yang terdeteksi kemudian digunakan untuk mengenali merek mobil dalam waktu singkat. Dalam penelitian ini kami menggunakan metode Single Shot Multibox Detector yang dikenal untuk deteksi objek yang berjalan di Aplikasi Jupyter Notebook. Data yang digunakan untuk penelitian ini bersifat publik yang didapat dari sumber dataset website Kaggle yang berisi dari beberapa jumlah gambar yang bervariasi. Terdapat 7 kelas merek mobil yaitu Volkswagen, Hyundai, Lexus, Mercedes, Peugeot, Renault, dan Tesla. Data pengujian pada penelitian ini menadapatkan 1.240 citra untuk kategori data latih dan 270 citra pada kategori data uji yang telah dilakukan pengujian dan menghasilkan nilai evaluasi dengan nilai akurasi terbaik sebesar 98.89 Persen dan nilai loss sebesar 0.025 persen.

Keywords


Logo; Single Shot Multibox Detector; Transportasi; Deteksi Objek; Mobil

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DOI: http://dx.doi.org/10.36448/jsit.v13i2.2660

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