Analisis Penggunaan Pra-proses pada Metode Transfer Learning untuk Mendeteksi Penyakit Daun Singkong

Authors

  • Amelia Devi Putri Ariyanto Institut Teknologi Sepuluh Nopember, Universitas Widya Husada
  • Salsabiil Hasanah Institut Teknologi Sepuluh Nopember
  • M. Bahrul Subkhi Institut Teknologi Sepuluh Nopember
  • Nanik Suciati Institut Teknologi Sepuluh Nopember

DOI:

https://doi.org/10.33633/tc.v22i2.7769

Keywords:

Transfer learning, Augmentation, Rotation, ResNet, MobileNet

Abstract

Singkong menjadi salah satu tanaman penting pada bidang agronomi dan banyak dikonsumsi oleh masyarakat. Namun, terdapat salah satu kendala dalam menjaga kelestarian tanaman singkong yaitu pendeteksian penyakit. Jika penyakit pada tanaman singkong dapat terdeteksi lebih dahulu melalui citra daunnya, maka penyakit tersebut dapat segera diobati. Proses klasifikasi dapat dilakukan untuk mendeteksi penyakit pada tanaman secara otomatis. Pada penelitian ini dilakukan klasifikasi tanaman singkong dengan menggunakan beberapa tahap pra-proses yaitu pra-proses dengan augmentasi, tanpa augmentasi dan pra-proses dengan rotasi, pada beberapa metode transfer learning seperti ResNet50 dan MobileNetV2. Penggunaan beberapa metode tersebut bertujuan untuk mencari metode mana yang memiliki hasil akurasi tertinggi. Penelitian menunjukkan bahwa MobileNetV2 tanpa augmentasi memberikan akurasi tertinggi sebesar 98.64% dalam mendeteksi penyakit tanaman singkong. Hal ini dapat menjadi referensi bagi peneliti selanjutnya dalam menentukan tahap pra-proses terbaik dalam metode transfer learning.

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Published

2023-05-26

Issue

Vol. 22 No. 2 (2023): Mei 2023

Section

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