Iswoyo, Dio Dwi (2025) IMPLEMENTASI MODEL YOLOV7 UNTUK KLASIFIKASI ACTION FIGURE GUNPLA. Undergraduate thesis, Universitas Nusantara PGRI Kediri.
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Abstract
Gunpla (Gundam Plastic Model) adalah action figure yang dirakit dari komponen terpisah dan memiliki keragaman desain tinggi, sehingga menyulitkan identifikasi manual, terutama pada varian yang memiliki kemiripan visual. Penelitian ini bertujuan mengembangkan sistem klasifikasi Gunpla menggunakan algoritma deteksi objek YOLOv7 yang diimplementasikan dalam aplikasi web berbasis Streamlit. Dataset terdiri dari tiga varian resmi, yaitu HG Barbatos, HG Barbatos Lupus, dan HG Barbatos Lupus Rex, dengan total 732 gambar. Model dilatih menggunakan Google Colab dan Roboflow, serta dievaluasi dengan metrik precision, recall, F1-score, dan mean Average Precision (mAP). Hasil pengujian menunjukkan sistem mampu mendeteksi Gunpla dengan akurasi tinggi, yakni precision 98,10%, recall 93,20%, F1-score 95,42%, dan mAP 99,23%. Sistem juga menampilkan informasi deskriptif tentang objek yang terdeteksi, memberikan pengalaman pengguna yang informatif dan interaktif. Penelitian ini membuktikan bahwa YOLOv7 efektif untuk mengenali objek visual kompleks seperti Gunpla dan bermanfaat bagi kolektor maupun pengguna umum.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | Gunpla, YOLOv7, deteksi objek, dataset gambar, Streamlit. |
Subjects: | 410 Engineering science > 459 Computer science 410 Engineering science > 462 Information technology 410 Engineering science > 463 Software engineering |
Divisions: | Fakultas Teknik dan Ilmu Komputer > S1-Teknik Informatika |
Depositing User: | Dio Dwi Iswoyo |
Last Modified: | 07 Aug 2025 06:03 |
URI: | http://repository.unpkediri.ac.id/id/eprint/20453 |
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