KLASIFIKASI DAGING SAPI DAN DAGING BABI MENGGUNAKAN ARSITEKTUR EFFICIENTNET-B3 DAN AUGMENTASI DATA - Maulana Junihardi; Jasril jasril; Suwanto Sanjaya; Lestari Handayani; Fadhilah Syafria (Jurnal Tekinkom (Teknik Informasi dan Komputer), 2023)
The increasing demand for beef has made its price soar. the traders then mix beef with pork to get more profit. There is a technology in the field of informatics that can be used to differentiate beef, pork and mixed meat. This research was conducted to find out the difference between beef, pork and mixed meat. In this study, a deep learning convolutional neural network with the EfficientNet-B3 architecture is used for image identification to distinguish between beef and pork. 9000 images have been divided into three categories: mixed meat, pork and beef. This study compares the classification results using original data and data augmentation. The data augmentation models used are brightness, rotation, and horizontal and vertical inversion. Data is split 80:20 and 90:10 for training and testing respectively. The best results are achieved by using a division ratio of 90:10 on image data with augmentation which has a learning rate of 0.01 and Adamax Optimizer which has accuracy, precision and recall levels of 98.66%, 98.67% and 98.66%.