Optimasi Klasifikasi Penyakit Daun Padi Menggunakan Arsitektur ConvNeXt_tiny dan Transfer Learning

• Muhammad Syofian
• 14230005

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ABSTRAK

ABSTRAK

• Nama               : Muhammad Syofian
• NIM                  : 14230005
• Program Studi : Magister Ilmu Komputer
• Jenjang           : Strata Dua (S2)

Konsentrasi : Artificial Intelligence & Blockchain Judul Tesis : Optimasi Klasifikasi Penyakit Daun Padi Menggunakan Arsitektur ConvNeXt_tiny dan Transfer Learning

Penelitian ini membahas optimalisasi model ConvNeXt_tiny dalam klasifikasi penyakit daun padi berbasis citra menggunakan pendekatan transfer learning. Deteksi penyakit daun secara otomatis menjadi penting dalam mendukung pertanian presisi dan pengendalian penyakit tanaman. Metode manual yang selama ini digunakan memiliki keterbatasan dalam hal kecepatan, akurasi, dan konsistensi, sehingga dibutuhkan solusi berbasis kecerdasan buatan untuk meningkatkan efisiensi dan efektivitas. Pada penelitian ini, citra daun padi yang terdiri dari 10 kelas penyakit diolah melalui tahapan preprocessing dan augmentasi, termasuk resizing, color jitter, rotasi acak, affine transformasi, crop acak, dan flip horizontal. Model ConvNeXt_tiny dilatih selama 5 epoch menggunakan dataset sebanyak 11.215 citra, dengan strategi fine-tuning dan transfer learning dari ImageNet. Evaluasi performa menunjukkan bahwa model ini mencapai akurasi dan F1-score sebesar 97,40%, melampaui beberapa arsitektur populer seperti EfficientNet, ResNet, dan MobileViTV2 dalam studi sebelumnya. Hasil ini menunjukkan bahwa ConvNeXt_tiny efektif digunakan sebagai model ringan dan akurat untuk klasifikasi citra daun padi, dengan potensi besar untuk diterapkan dalam sistem deteksi penyakit tanaman di dunia nyata.

                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           

KATA KUNCI

Keyword ConvNeXt_tiny dan Transfer Learning

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