Klasifikasi Bibit Sapi Peranakan Ongole Menggunakan Metode Pengolahan Citra

https://doi.org/10.22146/ijeis.15261

Leylin Fatqiyah(1), Agus Harjoko(2*)

(1) 
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author

Abstract


Ongole Crossbreed cattle is the largest cattle in Indonesia. Indonesian consume it’s beef in a large amount. Classification effects beef’s  quantity and quality. However, the classification process is measuring manually one by one all this time. Moreover the current standard is too high and inappropriate due to the real exist conditions. Seeing the importance of classification, it is necessary to make a system that is able to classify Ongole Crossbreed cattle stocker.

This system will measure quantitative requirement parameters from the image. This system will classify using image processing. Implementation of the system is using Matlab software. This system will classify into four classes, namely class I, class II, class III, and external class III. According to the results, it is obtained that the system is able to measure the body lenght, the chest circumference, and the height with accuracy rates are 90,77%, 93,30% and 93,13%. This system is able to classify the class of  Ongole Crossbreed cattle stocker with accuracy rate is 86,67%

Keywords


Image processing; Ongole Crossbreed cattle; classification

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References

[1] Badan Standarisasi Nasional, 2008, Standar Nasional Indonesia Bibit Sapi Peranakan Ongole, http://disnakkeswan.lampungprov.go.id/sni/sni_7356- 2008_bibit_sapi_po.pdf diakses pada tanggal 15 September 2012.

[2] Ahmad, U., Tjahjohutomo, R. dan Mardison, S., 2008, Pengembangan Mesin Sortasi Dan Pemutuan Buah Jeruk Dengan Sensor Kamera CCD, Prosiding Seminar Nasional Teknik Pertanian, Yogyakarta.

[3] Perwiranto, H., 2011, Sistem Klasifikasi Mutu Buah Tomat Menggunakan Pengolahan Citra Digital dan Jaringan Saraf Tiruan, Skripsi, FMIPA, UGM, Yogyakarta.

[4] Wiharja, Y. P., Harjoko, A, 2014, Pemrosesan Citra Digital untuk Klasifikasi Mutu Pisang Menggunakan Jaringan Saraf Tiruan, IJEIS, Vol.4, on.1, 2014

[5] Kadir, A dan Susanto, A, 2013, Teori dan Aplikasi Pengolahan Citra Digital, Penerbit Andi, Yogyakarta.

[6] Matlab Analyst, Imdistline, http://mathworks.com/help/images/ref/imdistline.html , diakses April 2014.

[7] Matlab Analyst, Imellipse, http://www.mathworks.com/help/images/ref/imellipse.html? searchHighlight=imelipse, diakses Oktober 2014.

[8] Paulus, E dan Nataliani, Y, 2007, GUI Matlab, Penerbit Andi, Yogyakarta.



DOI: https://doi.org/10.22146/ijeis.15261

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