Klasifikasi Penyakit Daun Jagung Menggunakan Fine Tuned Lightweight Deep Learning

• MERY OKTAVIYANTI PUSPITANINGTYAS
• 14230004

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ABSTRAK

ABSTRAK

• Nama        : Mery Oktaviyanti Puspitaningtyas
• NIM                  : 14230004
• Program Studi : Ilmu Komputer
• Fakultas          : Teknologi Informasi
• Jenjang           : Strata Dua (S2)

Peminatan : Artificial Intelligence & Blockchain Judul : Klasifikasi Penyakit Daun Jagung Menggunakan Fine Tuned Lightweight Deep Learning

Pengenalan penyakit daun jagung penting untuk mencegah penurunan hasil panen, namun identifikasi manual masih tidak efisien dan memerlukan waktu lama. Penelitian ini menggunakan metode deep learning berbasis arsitektur lightweight untuk mengembangkan sistem klasifikasi penyakit daun jagung dengan pendekatan transfer learning menggunakan empat model, yaitu MobileNetV1, MobileNetV2, MobileNetV3 Small, dan EfficientNetB0. Dataset publik digunakan untuk pelatihan dan validasi, sedangkan dataset pribadi digunakan sebagai data uji. Hasil menunjukkan bahwa model terbaik pada dataset publik adalah MobileNetV1 tanpa fine tuning dengan akurasi 97,87%, sedangkan pada dataset pribadi model terbaik adalah EfficientNetB0 dan MobileNetV1 dengan fine tuning yang mencapai akurasi 85,19%. Kesimpulannya, model lightweight dengan transfer learning juga efektif digunakan untuk klasifikasi penyakit daun jagung, namun tetap diperlukan penyesuaian lebih lanjut agar model lebih adaptif terhadap data lapangan

KATA KUNCI

Fine Tuned Lightweight Deep Learning

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DAFTAR PUSTAKA

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