Klasifikasi Kesegaran Daging Sapi Menggunakan Deep Learning Arsitektur VGG16 Dengan Augmentasi Citra

Elia, Benny
Darmawan, I Dewa Made Bayu Atmaja

Jurnal Nasional Teknologi Informasi dan Aplikasinya
Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022

Beef is one of the best foods to eat. However, to identify beef manually has a weakness, namely the limitations of human visual abilities. Therefore it is necessary to have an indicator of the level of freshness of the meat. This study uses image augmentation to change or modify images and use Convolutional Neural Network (CNN) with VGG16 architecture to perform image classification. The accuracy obtained with epoch 15 and the distribution of data by 80% of training data and 20% of validation data is the highest accuracy obtained, which is 97.14% and when tested with validation data it gets an accuracy of 98.68%. Overall, the model that has been used can classify the freshness of beef well.