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Convolutional Neural Network untuk Klasifikasi Citra Makanan Khas Indonesia

Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer

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ISSN 2548-964X
 
Authentication Code dc
 
Title Statement Convolutional Neural Network untuk Klasifikasi Citra Makanan Khas Indonesia
 
Added Entry - Uncontrolled Name Darojat, Muhammad Dandi
Sari, Yuita Arum
Wihandika, Randy Cahya
Fakultas Ilmu Komputer, Universitas Brawijaya
Fakultas Ilmu Komputer, Universitas Brawijaya
Fakultas Ilmu Komputer, Universitas Brawijaya
 
Summary, etc. 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.
 
Publication, Distribution, Etc. Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya
 
Electronic Location and Access application/pdf
http://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/10096
 
Data Source Entry Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer; Vol 5 No 11 (2021): November 2021
 
Language Note eng
 
Terms Governing Use and Reproduction Note Hak Cipta (c) 2021 Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
 


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