Klasifikasi Citra untuk Menentukan Daun Segar atau Daun Layu Menggunakan Vision Transformer (ViT) untuk Otomatisasi Proses Penyortiran Daun
DOI:
https://doi.org/10.22441/jitkom.v10i1.004Abstrak
Penelitian ini mengeksplorasi pemanfaatan arsitektur Vision Transformer (ViT) untuk klasifikasi citra daun ke dalam dua kategori, yaitu daun segar dan daun layu. Data yang digunakan berjumlah 3000 citra (gambar), diperoleh secara langsung melalui kamera smartphone, masing-masing terdiri dari 1.500 gambar daun segar dan 1.500 gambar daun layu. Model ViTForImageClassification dari Hugging Face Transformers dipilih sebagai kerangka utama, diimplementasikan menggunakan PyTorch dalam platform Google Colaboratory. 10% dataset digunakan sebagai data test guna menilai performa model yang telah melalui proses pelatihan sebelumnya sebesar 70% data train dan 20% data validasi. Berdasarkan hasil evaluasi, model ViT mampu melakukan klasifikasi dengan akurasi keseluruhan sebesar 88,9%, precision 90%, recall 89%, serta F1-score sebesar 89%. Temuan ini mengindikasikan bahwa pendekatan berbasis deep learning, khususnya Vision Transformer, memiliki potensi signifikan dalam mendukung proses penyortiran daun, pemantauan kesehatan tanaman, dan pengendalian mutu produk pertanian.Referensi
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