Joint proceedings of the 2nd and the 3rd International Conference on Food Security Innovation (ICFSI 2018-2019)

California Papaya Fruit Maturity Classification Uses Learning Vector Quantization

Authors
Romi Wiryadinata, Andy A. Fatmawaty, Muhammad Saepudin, Alimuddin, Oktavia Widia Ningrum, Imamul Muttakin
Corresponding Author
Romi Wiryadinata
Available Online 4 March 2021.
DOI
10.2991/absr.k.210304.045How to use a DOI?
Keywords
Classification of maturity, Papaya California, Learning Vector Quantization
Abstract

This research aims to build a system for the classification of papaya maturity level using Learning Vector Quantization. The classification process is done by the colour feature extraction value. Forty-five images consist of 30 images for training data and 15 images for test data were used. The images were divided into 3 classes: rip, mature and raw. The parameters for classification are mean, skewness, and kurtosis. Test results 1 obtained an accuracy of 60% consisting of 9 true images and 6 incorrect images with hidden layer 5 and learning rate 0,1. Test results 2 obtained an accuracy of 66,67% consisting of 10 true images and 5 incorrect images with hidden layer 10 and learning rate 0,5. Test image data are 15 papaya images consisting of 5 mature images, 5 imperfect images, and 5 raw images.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Joint proceedings of the 2nd and the 3rd International Conference on Food Security Innovation (ICFSI 2018-2019)
Series
Advances in Biological Sciences Research
Publication Date
4 March 2021
ISBN
978-94-6239-346-2
ISSN
2468-5747
DOI
10.2991/absr.k.210304.045How to use a DOI?
Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Romi Wiryadinata
AU  - Andy A. Fatmawaty
AU  - Muhammad Saepudin
AU  - Alimuddin
AU  - Oktavia Widia Ningrum
AU  - Imamul Muttakin
PY  - 2021
DA  - 2021/03/04
TI  - California Papaya Fruit Maturity Classification Uses Learning Vector Quantization
BT  - Joint proceedings of the 2nd and the 3rd International Conference on Food Security Innovation (ICFSI 2018-2019)
PB  - Atlantis Press
SP  - 243
EP  - 247
SN  - 2468-5747
UR  - https://doi.org/10.2991/absr.k.210304.045
DO  - 10.2991/absr.k.210304.045
ID  - Wiryadinata2021
ER  -