Implementasi Sistem Smart Hidroponik Berbasis IoT dan YOLOv8-TFLite untuk Pemantauan Nutrisi dan Deteksi Penyakit Tanaman Pakcoy
Authors
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Najhan Ibra Susatiawan
Universitas Negeri Padang
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Ahmaddul Hadi
Universitas Negeri Padang
DOI:
https://doi.org/10.36312/3ycfg720Keywords:
Hidroponik, Internet of Things (IoT), YOLOv8, Android, Deteksi Penyakit TanamanAbstract
Keberhasilan budidaya hidroponik sangat bergantung pada kestabilan parameter lingkungan seperti pH dan nutrisi (TDS), serta pemantauan kesehatan visual tanaman yang seringkali masih dilakukan secara manual. Penelitian ini bertujuan untuk mengembangkan sistem pemantauan dan perawatan otomatis tanaman pakcoy hidroponik berbasis Internet of Things (IoT) dan algoritma You Only Look Once (YOLO). Penelitian menggunakan pendekatan prototype dengan mengintegrasikan mikrokontroler ESP32, sensor pH, TDS, dan DHT11 yang terhubung ke Firebase dan aplikasi Android. Model YOLOv8-TFLite diimplementasikan pada aplikasi untuk mendeteksi penyakit melalui 1.271 citra daun yang terbagi ke dalam 5 kondisi kelas (sehat, tidak sehat, serta indikasi defisiensi nutrisi, serangan hama, dan penyakit daun). Hasil pengujian sistem kendali closed-loop menunjukkan bahwa aktuator mampu menstabilkan anomali pH dan TDS dalam durasi rata-rata kurang dari 60 detik untuk setiap skenario, yaitu pada kondisi pH asam, pH basa, dan TDS rendah. Evaluasi model YOLOv8-TFLite menunjukkan akurasi 93,7% dalam mengklasifikasikan kondisi daun. Sinergi antara pemantauan IoT dan diagnostik visual AI ini memberikan implikasi praktis bagi petani hidroponik skala kecil-menengah, yaitu berupa sistem pendukung keputusan (decision support system) yang otomatis, terjangkau, dan mudah dioperasikan tanpa memerlukan pengetahuan teknis mendalam.
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