Abstract
This research aims to develop a system that can identify diseases in strawberry plants using Convolutional Neural Network (CNN) method. Strawberry plants have high economic value but are often attacked by diseases that can lead to crop failure. The use of CNN in classifying diseases in strawberry leaf images has successfully demonstrated high accuracy. A dataset consisting of six types of strawberry diseases has been used in this study. The CNN model training process was conducted using preprocessed datasets and produced satisfactory accuracy rates. The evaluation results show that the CNN model is capable of classifying strawberry diseases with an accuracy rate of 97.5% on the training data and 96% on the validation data. The implementation of this CNN model has great potential to assist farmers in detecting diseases in strawberry plants early and reducing crop failure rates