Penerapan Metode CNN (Convolutional Neural Network) Dalam Mengklasifikasi Jenis Ubur-Ubur
DOI:
https://doi.org/10.55606/juprit.v2i4.3084Keywords:
Convolutional Neural Network (CNN), jellyfish, classification, identification, Hard Sequential ModelAbstract
The purpose of this research is to apply the Convolutional Neural Network (CNN) method to classify various types of jellyfish. Jellyfish as sea creatures have a variety of shapes and sizes. This research includes data acquisition, data pre-processing, classification, and evaluation. The Keras Sequential model was chosen to implement the CNN model in this study. The results of the study showed an accuracy rate of 87%. In addition, the CNN model training accuracy rate reached 0.9037 with a loss value of 0.2097, while in CNN model testing, the accuracy rate reached 0.7944 with a loss of 0.5228.
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