Perancangan Sistem Pendeteksi Penyakit Pada Rumput Laut Dengan Menggunakan Metode Convolutional Neural Network

Mhd Adi Setiawan Aritonang; Muhammad  Abrar Masril; Deosa  Chaniago; Muhammad  Marshall Al Karim; Viriya  Mahani Cunis; Surgiwe

doi:10.55382/jurnalpustakaai.v5i2.1160

Penulis

Mhd Adi Setiawan Aritonang Institut Teknologi Batam
Muhammad Abrar Masril Institut Teknologi Batam
Deosa Chaniago Institut Teknologi Batam
Muhammad Marshall Al Karim Institut Teknologi Batam
Viriya Mahani Cunis Institut Teknologi Batam
Surgiwe Institut Teknologi Batam

DOI:

https://doi.org/10.55382/jurnalpustakaai.v5i2.1160

Kata Kunci:

Deteksi Penyakit Rumput Laut, Convolutional Neural Network (CNN), YOLO v11, Ultralytics, Flask

Abstrak

Penelitian ini mengembangkan sistem deteksi penyakit pada rumput laut menggunakan metode Convolutional Neural Network (CNN) dengan YOLO v11. Sistem dilatih menggunakan data yang terdiri dari Healthy Seaweed, Kerak Bryozoan, dan ice-ice dari dataset Roboflow. Model YOLO v11m dengan 20 juta parameter dievaluasi menggunakan metrik presisi, recall, F1-Score, dan mAP. Hasil menunjukkan kinerja yang baik dalam deteksi penyakit dengan mAP50 sekitar 0.84 pada data validasi dan implementasi dalam aplikasi Web menggunakan Flask

Unduhan

Data unduhan belum tersedia.

Referensi

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