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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Yuita Arum Sari
Faculty of Computer Science, Brawijaya University
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Convolutional Neural Network untuk Klasifikasi Citra Makanan Khas Indonesia Muhammad Dandi Darojat; Yuita Arum Sari; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 11 (2021): November 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

There are various types of special food in Indonesia that are still difficult to identify domestically and internationally. If many people know the special Indonesian food, then Indonesia will be increasingly recognized as well. In line with this, state revenue may increase as well. But in some cases, special food in Indonesia is still challenging to identify, especially for foreign tourists. This paper proposes an image classification system for Indonesian special food images using the Convolutional Neural Network algorithm (CNN) which is supported by several other methods and algorithms. Based on the experiments conducted eight times on 26 models, the best model was obtained with a test accuracy value of 0.6 and an evaluation accuracy of 0.91. This shows that the CNN is relatively good to be applied to the classification of special Indonesian food images.
Co-Authors Muhammad Dandi Darojat Randy Cahya Wihandika