Penerapan Model EfficientNetV2-B0 pada Benchmark IP102 Dataset untuk Menyelesaikan Masalah Klasifikasi Hama Serangga
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Abstract
Hama serangga merupakan masalah yang sering di hadapi oleh petani. Karena ukurannya yang kecil dan jenis spesiesnya banyak. tak jarang petanipun kesulitan untuk menjaga tanaman mereka dari ancaman hama serangga karena penanganannya tidak memakai satu obat, melainkan dengan mencocokan spesies serangga. Sehingga karena banyaknya obat pembasmi, petanipun bingung obat mana yang tepat. Di dalam penelitian ini, telah di coba penggunaan metode deep learning arsitektur model EfficientNetV2 B0 pada dataset IP102 yang berkarakteristik imbalance dan ada jenis serangga yang identik antara satu dengan yang lain. Penelitian ini bertujuan untuk mengeksplorasi kemungkinan model kecil yang dapat di implementasikan di smartphone atau IOT yang mudah di bawa ke ladang pertanian tanpa tergantung pada internet. Model terbaik yang berhasil dibuat memperoleh akurasi 51% dengan F1-Score 50.14%.
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