Optimalisasi Convolutional Neural Network Menggunakan Augmentasi dan Hyperparameter untuk Klasifikasi Daging Sapi dan Daging Babi
DOI:
https://doi.org/10.26418/justin.v12i4.80337Keywords:
Augmentasi, daging babi, daging sapi, EfficientNet-B0, hyperparameterAbstract
Tujuan penelitian ini adalah untuk menentukan model optimal pada klasifikasi sapi dan babi dengan menerapkan augmentasi data serta hyperparameter pada Convolutional Neural Network (CNN) arsitektur EfficientNet-B0. Data citra daging sapi dan daging babi yang diambil langsung dari beberapa pasar yang ada di kota Pekanbaru. Data diambil menggunakan kamera DSLR dan kamera smartphone dengan jarak antara 10cm sampai 15cm dan pencahayaan menyesuaikan dengan kondisi cahaya pada lingkungan pasar. Proses pelatihan dan pengujian model klasifikasi menggunakan beberapa skenario yaitu kombinasi pembagian data, jenis dataset, optimizer, fungsi aktivasi, dan learning rate. Berdasarkan hasil pengujian, model klasifikasi yang memiliki nilai akurasi tertinggi adalah 0,93 yaitu model dengan skenario jenis dataset gabungan (dataset original ditambah dengan dataset hasil augmentasi) dengan pembagian data 90% data latih dan 10% data uji. Hasil pengujian akurasi tertinggi menunjukkan model tidak overfitting, tetapi masih ada beberapa data citra daging sapi yang diklasifikasikan menjadi daging babi ataupun oplosan, sehingga perlu dilakukan penelitian lebih lanjut untuk meminimalkan masalah tersebut karena sebagai seorang muslim harus memastikan daging sapi yang dimakan adalah benar daging sapi.References
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