Identifikasi Penyakit Pada Tanaman Kopi Berdasarkan Citra Daun Menggunakan Metode Convolution Neural Network

  • Ahmad Fatchurrachman Universitas Multi Data Palembang
  • Daniel Udjulawa Universitas Multi Data Palembang
Keywords: Adam, CNN, Coffee, Optimizer, ResNet-50

Abstract

Coffee plants are usually made for drinks made from coffee beans that have been ground into powder. One of the causes of decreased coffee quality is caused by pests that can attack from the leaves, stems and roots. This study aims to identify coffee plant diseases based on leaves using the Convolution Neural Network (CNN) method with the ResNet-50 architecture with the Adam optimizer. The total data from the dataset is 1664 images, in the dataset there are 1264 train data images and 400 test images. The highest result in training in this study using 60 epochs and Adam's optimizer with a probability value of learning_rate of 0.0001 getting a probability value of 0.9969 and the lowest value getting a probability value of 0.4918. The results of testing the test data in this study obtained an accuracy rate of 99%.

Published
2023-04-11
How to Cite
Fatchurrachman, A., & Udjulawa, D. (2023, April 11). Identifikasi Penyakit Pada Tanaman Kopi Berdasarkan Citra Daun Menggunakan Metode Convolution Neural Network. Jurnal Algoritme, 3(2), 151 -. https://doi.org/https://doi.org/10.35957/algoritme.v3i2.3384