Klasifikasi Daging Sapi dan Daging Babi Menggunakan CNN dengan Arsitektur EfficientNet-B4 dan Augmentasi Data

Authors

  • Ahmad Paisal Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Jasril Jasril Universitas Islam Negeri Sultan Syarif Kasim Riau http://orcid.org/0000-0002-6937-2078
  • Suwanto Sanjaya Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Lestari Handayani Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Fadhilah Syafria Universitas Islam Negeri Sultan Syarif Kasim Riau

DOI:

https://doi.org/10.32493/informatika.v8i2.30586

Keywords:

Augmentasi, EfficientNet-B4, CNN, Klasifikasi, Daging

Abstract

Meningkatnya kebutuhan daging sapi, membuat harga daging sapi melonjak. Banyak pedagang melakukan kecurangan dengan melakukan oplos daging sapi dengan daging babi agar mendapatkan keuntungan yang lebih. Salah satu teknologi dalam bidang informatika dapat dimanfaatkan untuk membantu membedakan daging sapi, daging babi, dan daging oplosan. Dengan cara klasifikasi hal ini dapat dilakukan, penelitian ini menggunakan Convolutional Neural Network dengan arsitektur EfficietnNet-B4. Proses augmentasi data juga dilakukan pada penelitian ini untuk memperbanyak data citra, setelah di-augmentasi total citra menjadi 9000 dari 3 kelas. Pembagian dataset pada penelitian ini dibagi menjadi 2 yaitu 80% data latih dan 20% data uji serta 90% dan 10%. Proses pengujian dilakukan dengan memfokuskan model yang mendapatkan validation accuracy diatas 75% pada proses pelatihan. Hasil percobaan pada dataset 80:20 citra dengan augmentasi lebih unggul pada setiap model dibanding dengan citra asli. Sedangkan pada dataset 90:10 hasil percobaan dengan citra asli rata – rata lebih unggul dibanding citra dengan augmentasi.

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Jurnal Informatika Universitas Pamulang Vol. 8 No. 2 Juni 2023

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2023-06-30

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Vol. 8 No. 2 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG

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