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Deteksi Kualitas Telur Menggunakan Analisis Tekstur
https://doi.org/10.22146/ijccs.24756 Enny Itje Sela(1*), M Ihsan(2)
(1) Universitas Teknologi Yogyakarta
(2) STMIK AKAKOM, Yogyakarta
(*) Corresponding Author
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%.
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[1] Yuwanta, T., 2010, Telur dan Kualitas Telur, Gadjah Mada University Press, Yogyakarta.
[2] Soeparno, 2011, Dasar Teknologi Hasil Ternak, Gadjah Mada University Press, Yogyakarta.
[3] Sela, E.I., Widyaningrum, R., 2015, Osteoporosis Detection Using Important Shape-Based Features Of The Porous Trabecular Bone On The Dental X-Ray Images, Interl. Journal of Advanced Computer Science and Apllications (IJACSA), Vol 1 No 6.
[4] Sela, E.I., Hartati, S., Harjoko, A., Wardoyo, R., Mudjosemedi, M, 2015, Features Selection Of The Combination Of Porous Trabecular With Anthropometic Fetaures For Osteoporosis Screening, Interl. Journal Electrical and Computer Engineering (IJECE), Vol. 5 No 1.
[5] Sela, E.I., Hartati, S., Harjoko, A., Wardoyo, R., Mudjosemedi, M., 2013, Segmentation On Periapical Dental X-Ray For Osteoporosis Screening, International Journal of Advanced Computer Sciences and Applications (IJACSA), Vol 4 No 7.
[6] Prahara, H., Sela, E.I, 2016, Identifikasi Tingkat Kematangan Buah Pepaya Menggunakan Jaringan Syaraf Tiruan Learning Vector Quantization, Seminar Nasional Riset Teknologi Informasi (SRITI), STMIK AKAKOM Yogyakarta.
[7] Trisnaningtyas, P.R., Maimunah, 2015, Klasifikasi Mutu Telur Berdasarkan Kebersihan Kerabang Telur Menggunakan K-Nearest Neighbor, Universitas Islam “45”, Bekasi.
[8] A. Sugiharto, 2016, Pemodelan Deteksi Kualitas Telur Berbasis Citra, Skripsi STMIK AMIKOM, Yogyakarta.
[9] Ruslianto,I, 2013, Klasifikasi Telur Ayam dan Telur Burung Puyuh Menggunakan Metode Connected Component Analysis, Skripsi, STMIK Pontianak, Kalimantan Barat.
[10] H. Herman and A. Harjoko, “Pengenalan Spesies Gulma Berdasarkan Bentuk dan Tekstur Daun Menggunakan Jaringan Syaraf Tiruan,” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 9, no. 2, p. 207, Jul. 2015 [Online]. Available: https://jurnal.ugm.ac.id/ijccs/article/view/7549. [Accessed: 03-May-2017]
[11] N. M. Setiohardjo and A. Harjoko, “Analisis Tekstur untuk Klasifikasi Motif Kain (Studi Kasus Kain Tenun Nusa Tenggara Timur),” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 8, no. 2, pp. 177–188, 2014 [Online]. Available: https://jurnal.ugm.ac.id/ijccs/article/view/6545. [Accessed: 03-May-2017]
DOI: https://doi.org/10.22146/ijccs.24756
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