Klasifikasi Varietas Biji Kedelai Menggunakan Convolutional Neural Network Berbasis EfficientNetV2B2 pada Citra Digital

Authors

  • ardan putra ramadhan Universitas Universitas Nusantara PGRI Kediri Indonesia
  • Patmi Kasih Universitas Universitas Nusantara PGRI Kediri Indonesia
  • Muh Aris Saputra Universitas Universitas Nusantara PGRI Kediri Indonesia

DOI:

https://doi.org/10.29407/ec3yxe08

Abstract

Kedelai merupakan komoditas pangan penting yang banyak dimanfaatkan sebagai bahan baku industri pangan di Indonesia. Identifikasi varietas biji kedelai secara manual masih memiliki keterbatasan karena bergantung pada pengamatan manusia dan berpotensi menimbulkan kesalahan. Penelitian ini bertujuan untuk mengembangkan sistem klasifikasi varietas biji kedelai berbasis citra digital menggunakan metode Convolutional Neural Network dengan arsitektur EfficientNetV2B2 . Dataset yang digunakan terdiri atas citra varietas kedelai lokal yang melalui tahapan preprocessing berupa resize, normalisasi, dan data augmentation. Model dikembangkan menggunakan pendekatan transfer learning dan dievaluasi menggunakan accuracy, precision, recall, F1-score, serta confusion matrix. Hasil pengujian menunjukkan bahwa model mampu mengklasifikasikan varietas biji kedelai dengan tingkat akurasi sebesar 74,13 persen. Hasil tersebut menunjukkan bahwa EfficientNetV2B2 cukup efektif untuk mendukung proses identifikasi varietas biji kedelai secara otomatis dan konsisten.

Keywords:

Convolutional Neural Network, EfficientNetV2B2, Kedelai, Klasifikasi Citra, Transfer Learning

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Published

2026-07-20

Issue

Vol. 10 No. 1 (2026): Prosiding Seminar Nasional Inovasi Teknologi Tahun 2026

Section

Articles

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How to Cite

Klasifikasi Varietas Biji Kedelai Menggunakan Convolutional Neural Network Berbasis EfficientNetV2B2 pada Citra Digital. (2026). Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 10(1), 345-354. https://doi.org/10.29407/ec3yxe08