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Rancang Bangun Alat Monitoring Jumlah Ayam Potong (Broiler) dan Deteksi Suhu Kandang Berbasis Internet of Things (IoT)

Muhammad Ikhsan
Payakumbuh State Agricultural Polytechnic ROR
Indonesia
Romy Aulia
Payakumbuh State Agricultural Polytechnic ROR
Indonesia
Syukriadi
Payakumbuh State Agricultural Polytechnic ROR
Indonesia
DOI: https://doi.org/10.59435/jgcs.v2i2.2026.77

Abstract

Penelitian ini mengembangkan sistem berbasis *Internet of Things* (IoT) untuk penghitungan ayam pedaging dan pengendalian suhu kandang. ESP32-CAM mengambil gambar melalui *endpoint* pengambilan HTTP, sedangkan inferensi YOLOv8n dijalankan pada komputer lokal menggunakan Python, OpenCV, dan Ultralytics. Dataset mencakup 2.339 gambar berukuran 1280 × 1280 piksel dan 78.286 anotasi ayam pedaging, yang dibagi menjadi 1.819 gambar pelatihan (77,77%) dan 520 gambar validasi (22,23%); tidak tersedia pembagian data uji independen. Pelatihan menggunakan 100 *epoch*, ukuran *batch* 16, dan input 640 × 640. Pada *epoch* terbaik, nilai presisi, *recall*, F1-*score*, mAP@0,5, dan mAP@0,5:0,95 pada tahap validasi masing-masing adalah 96,57%, 96,34%, 96,45%, 97,84%, dan 68,71%. Lima skenario penghitungan menghasilkan akurasi agregat 97,00%, MAE sebesar 0,60 ekor ayam/gambar, dan MAPE sebesar 3,00%. Kalibrasi suhu menghasilkan MAE sebesar 0,14 °C, sementara penghitungan otomatis mengurangi waktu pemrosesan sebesar 89,35% dibandingkan dengan penghitungan manual. Perintah Telegram untuk pengambilan gambar, penghitungan, dan akses *live-stream* berfungsi dengan baik dalam uji fungsional tunggal. Data uji independen, spesifikasi perangkat, deret waktu suhu, latensi, dan keandalan komunikasi masih diperlukan sebelum dapat membuat klaim umum mengenai kinerja *real-time*.

Keywords: IoT ESP32-CAM YOLOv8 Ayam Broiler Monitoring Suhu

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© Muhammad Ikhsan, Romy Aulia, Syukriadi (Author) 2026

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