Deteksi Kelayakan Telur Ayam Menggunakan Metode YOLOv8 Melalui Fitur Upload Gambar

Authors

  • Intan Nurafi Oktavia Universitas Nusantara PGRI Kediri Indonesia
  • Ahmad Bagus Setiawan Universitas Nusantara PGRI Kediri Indonesia
  • Intan Nur Farida Universitas Nusantara PGRI Kediri Indonesia

DOI:

https://doi.org/10.29407/e2re1a18

Abstract

Proses penyortiran telur di peternakan masih banyak dilakukan secara manual sehingga membutuhkan waktu yang relatif lama dan berpotensi menimbulkan kesalahan dalam mendeteksi kondisi telur. Penelitian ini bertujuan mengembangkan sistem deteksi kelayakan telur ayam berbasis web menggunakan algoritma YOLOv8 melalui fitur upload gambar. Metode yang digunakan adalah Research and Development (R&D) dengan model pengembangan Waterfall. Dataset terdiri dari citra telur layak dan telur retak yang diperoleh melalui pengambilan gambar langsung serta dataset pendukung dari Roboflow. Tahapan penelitian meliputi pengumpulan data, preprocessing, pelatihan model, dan pengujian sistem. Model dilatih menggunakan pembagian data latih 80% dan data uji 20% selama 100 epoch. Hasil penelitian menunjukkan bahwa model mampu mendeteksi dan mengklasifikasikan telur layak dan telur retak dengan accuracy 97,8%, precision 96,7%, recall 94,6%, dan F1-score 95,8%. Sistem berbasis web yang dikembangkan dapat membantu proses penyortiran telur menjadi lebih efektif dan konsisten melalui analisis gambar yang diunggah pengguna.

Keywords:

deteksi objek, kelayakan telur, unggah gambar, web, YOLOv8

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References

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Published

2026-07-20

Issue

Vol. 10 No. 1 (2026): Prosiding Seminar Nasional Inovasi Teknologi Tahun 2026

Section

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How to Cite

Deteksi Kelayakan Telur Ayam Menggunakan Metode YOLOv8 Melalui Fitur Upload Gambar. (2026). Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 10(1), 611-617. https://doi.org/10.29407/e2re1a18