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All Journal Jurnal Penelitian Rumpun Ilmu Teknik
Yohanna Permata Putri Pasaribu
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Computer Science & IT Engineering

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Penerapan Metode CNN (Convolutional Neural Network) Dalam Mengklasifikasi Jenis Ubur-Ubur Sandy Andika Maulana; Shabrina Husna Batubara; Tasya Ade Amelia; Yohanna Permata Putri Pasaribu
Jurnal Penelitian Rumpun Ilmu Teknik Vol. 2 No. 4 (2023): November : Jurnal Penelitian Rumpun Ilmu Teknik
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juprit.v2i4.3084

Abstract

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.
Co-Authors Sandy Andika Maulana Shabrina Husna Batubara Tasya Ade Amelia