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All Journal Indonesian Journal of Artificial Intelligence and Data Mining
Isnan Mellian Ramadhan
UIN Sultan Syarif Kasim Riau
Computer Science & IT

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Image Classification of Beef and Pork Using Convolutional Neural Network Architecture EfficienNet-B1 Isnan Mellian Ramadhan; Jasril - Jasril; Suwanto Sanjaya; Febi Yanto; Fadhilah Syafria
Indonesian Journal of Artificial Intelligence and Data Mining Vol 6, No 1 (2023): Maret 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v6i1.21843

Abstract

The increasing demand for beef has made many meat traders mix beef with pork to get more profit. Mixing beef and pork is harmful, especially for Muslims. In this study, the EfficientNet-B1 Convolutional Neural Network (CNN) approach was used to classify beef and pork. Experiments were conducted to compare accuracy using original data (without data augmentation) and with data augmentation. The data augmentation techniques used are rotation and horizontal flip. The total dataset after the data augmentation process is 3000 images. Many different settings were tested, including learning rates (0.00001, 0.0001, 0.001, 0.01, 0.1), batch size (32, 64), and optimizer (Adam, Adamax). After testing the Confusion Matrix, the highest accuracy results were obtained using data augmentation with a batch size of 32 of 98%. Meanwhile, those without data augmentation were 96%
Co-Authors Fadhilah Syafria Febi Yanto Jasril Jasril Suwanto Sanjaya