📅 24 June 2024
DOI: 10.61132/uranus.v1i2.172
Implementasi Metode Convolutional Neural Network (CNN) untuk Klasifikasi Jenis Ras Kucing
Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Asosiasi Riset Teknik Elektro dan Informatika Indonesia (ARTEII)
📄 Abstract
This research implements the Convolutional Neural Network (CNN) method to classify the various types of cat breeds that are common in Indonesia. This research attempts to create an automatic system that can definitely and accurately classify and identify the types of cat breeds that exist in Indonesia using image processing techniques. The data used contains a total of 600 images with each folder containing 200 images. Using this CNN method produces a validation accuracy rate of 54% in the process of classifying cat breeds. Research shows that further developing the image processing process will increase the accuracy value of the resulting system.
🔖 Keywords
#Classification of cat breeds in Indonesia; Convolutional Neural Network; Image Processing
ℹ️ Informasi Publikasi
Tanggal Publikasi
24 June 2024
Volume / Nomor / Tahun
Volume 2, Nomor 2, Tahun 2024
📝 HOW TO CITE
Aliefah Syalma Ratsdea Muftti; Yovi Litanianda, "Implementasi Metode Convolutional Neural Network (CNN) untuk Klasifikasi Jenis Ras Kucing," Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika, vol. 2, no. 2, Jun. 2024.
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