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Open access Jurnal SINTA 2

Deteksi Kualitas Telur Menggunakan Analisis Tekstur

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 11 No. 2 (2017) · pp. 199–208

DOI
10.22146/ijccs.24756
ISSN
2460-7258, 1978-1520
Published
2017-07-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Currently to find out the quality of eggs was conducted on visual observation directly on the egg, both the outside of the egg in the form of eggshell conditions or the inside of the egg by watching out using sunlight or a flashlight. This method requires good accuracy, so in the process it can affect results that are not always accurate. This is due to the physical limitations of each individual is different. This study examines the utilization of digital image processing for the detection of egg quality using eggshell image.The feature extraction method performed a texture feature based on the histogram that is the average intensity, standard deviation, skewness, energy, entropy, and smoothness properties. The detection method for training and testing is K-Means Clustering algorithm. The results of this application are able to help the user to determine the quality of good chicken eggs and good quality chicken eggs, with accurate introduction of good quality eggs by 90% and poor quality eggs by 80%.

Keywords

Collaboration network of the authors

8 authors · 14 co-authorship links · 6 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Teknologi Yogyakarta
  • Sunan Kalijaga State Islamic University Yogyakarta
  • Mulawarman University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Saucha DiwandariUniversitas Teknologi Yogyakarta1
Briyan Efflin SyahputraUniversitas Teknologi Yogyakarta1
Nathaniela Aptanta ParamaUniversitas Teknologi Yogyakarta1
Anindita SeptiariniMulawarman University1
Tundo TundoSunan Kalijaga State Islamic University Yogyakarta1
Riolandi AkbarSunan Kalijaga State Islamic University Yogyakarta1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Deteksi Kualitas Telur Menggunakan Analisis Tekstur</dc:title>
	<dc:creator>Sela, Enny Itje</dc:creator>
	<dc:creator>Ihsan, M</dc:creator>
	<dc:subject xml:lang="en-US">computer science</dc:subject>
	<dc:subject xml:lang="en-US">eggs, energy, entropy, texture analysis, K-Means, mean, skewness, standard deviation intensity, smoothness</dc:subject>
	<dc:description xml:lang="en-US">Currently to find out the quality of eggs was conducted on visual observation directly on the egg, both the outside of the egg in the form of eggshell conditions or the inside of the egg by watching out using sunlight or a flashlight. This method requires good accuracy, so in the process it can affect results that are not always accurate. This is due to the physical limitations of each individual is different. This study examines the utilization of digital image processing for the detection of egg quality using eggshell image.The feature extraction method performed  a texture feature based on the histogram that is the average intensity, standard deviation, skewness, energy, entropy, and smoothness properties. The detection method for  training and testing is  K-Means Clustering algorithm. The results of this application are able to help the user to determine the quality of good chicken eggs and good quality chicken eggs, with accurate introduction of good quality eggs by 90% and poor quality eggs by 80%.</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2017-07-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/24756</dc:identifier>
	<dc:identifier>10.22146/ijccs.24756</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 199-208</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/24756/16696</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2017 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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