Metode Moment Invariant Geometrik untuk Menganalisis Jenis Daging Babi dan Daging Sapi

*Oky Dwi Nurhayati -  Universitas Diponegoro, Indonesia
Isti Pudji hastuti -  Universitas Diponegoro, Indonesia
Received: 11 Sep 2018; Published: 30 Oct 2018.
Open Access
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Section: Research Articles
Language: EN
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Abstract
Beef needs have increased every year. So as the need for expensive beef even at certain times tends to rise. This is used by cheat seller to mix beef with pork because pork is relatively cheaper. This is very detrimental to consumers. Visually, many peoples (consumers) couldn’t distinguish these two types of meat. Hence, we conduct research to distinguish both types of meat.  One way to overcome these problems is the use of complete image processing techniques. The aim of this research was establised an application prototype to distinguish beef and pork with image processing techniques. Image processing method is used to distinguish the types of meat done by pre-processing, segmentation, feature extraction with geometrical moment invariant and K-NN classification. Geometric moment invariant method proposed to analyze beef and pork is done by extracting unique values from each images. This method can be used as a description of the form based on the moment theory. The results showed that the image processing method and K-NN classification with a value of k = 3 used in the research could significantly  used to analyze the type of meat namely beef and pork. The other difference can be shown from the phi moment invariant value, especially the value of phi (1) and phi (2)

 

Keywords
Beef; Pork; Geometric moment invariant; Image processing; K-NN classification

Article Metrics:

  1. Agusta, Y., 2007, K-Means - Penerapan, Permasalahan dan Metode Terkait, J. Sist. dan Inform.
  2. Assifa, F., 2017, Polisi Jember Tangkap Penjual Daging Sapi yang Dicampur Daging Babi, http://regional.kompas.com/read/2017/02/22/06265601/polisi.jember.tangkap.penjual.daging.sapi.yang.dicampur.daging.babi, diakses tanggal 14 Mei.
  3. Astuti, W., 2016, Klasifikasi Citra Daging Sapi Dan Daging Babi Berdasarkan Ciri Warna Dan Tekstur, Skripsi thesis UIN Sunan Kalijaga, Yogyakarta, http://digilib.uin-suka.ac.id/22203/
  4. As Syaukani, M., 2009, Mengenal Beda Daging Sapi dan Daging Babi, Hidayatullah.
  5. Budianita, E., Jasril, J., dan Handayani, L., 2015. Implementasi Pengolahan Citra dan Klasifikasi K-Nearest Neighbour Untuk Membangun Aplikasi Pembeda Daging Sapi dan Babi Berbasis Web, J. Sains dan Teknol. Ind., vol. 12, no. Vol 12, No 2, Juni, 242–247.
  6. BSN, 2008. Standar Nasional Indonesia 3932:2008 Mutu karkas dan daging sapi. Standar Nas. Indones., pp. 1–14.
  7. Falah, R. F., Nurhayati, O. D., dan Martono, K. T., 2016, Aplikasi Pendeteksi Kualitas Daging Menggunakan Segmentasi Region of Interest Berbasis Mobile, J. Teknol. dan Sist. Komput., vol. 4, no. 2, pp. 333–343.
  8. Food and Agriculture Organization, Composition of Meat, 2017. http://www.fao.org/ag/againfo/themes/en/meat/backgr_composition.html, diakses tanggal 23 Mei.
  9. Gonzalez, R. C., dan Woods, R.E., Digital Image Processing. Pearson Education, 2008.
  10. Irwanto, 2012, Optimasi Kinerja Algoritma Klasterisasi K-Means untuk Kuantisasi Warna Citra, Fakultas Teknologi Informasi, Institut Teknologi Sepuluh Nopember, Surabaya.
  11. Jain, A., 1989, Fundamentals of digital image processing.
  12. Komariah, S. Rahayu, dan Sarjito, 2009, Sifat Fisik Daging Sapi, Kerbau Dan Domba Pada Lama Postmortem yang Berbeda. Jurnal Peternakan, vol. 33, no. 3, 183–189.
  13. Lawrie, R.A., 1995, Ilmu Daging Diterjemahkan oleh Aminuddin Prakkasi, Universitas Indonesia Press, Jakarta.
  14. Mas'ud, 2015, Implementasi Principal Component Analysis (PCA) dan Euclidean Distance untuk Identifikasi Citra Daging Sapi dan Daging Babi, Skripsi S-1, Universitas Dian Nuswantoro, Semarang.
  15. Muzami, A., Nurhayati, O. D., dan Martono, K. T., 2016, Aplikasi Identifikasi Citra Telur Ayam Omega-3 Dengan Metode Segmentasi Region Of Interest Berbasis Android, J. Teknol. dan Sist. Komput., vol. 4, no. 2, pp. 380–388.
  16. Putra, D., 2010, Pengolahan Citra Digital. Yogyakarta: Penerbit ANDI.
  17. Wahyudiyanta, I., 2017. Begini Cara Membedakan Daging Sapi dan Babi, http://news.detik.com/jawatimur/3218862/begini-cara-membedakan-daging-sapi-dan-babi, diakses tanggal 16 Mei.
  18. Wibowo, S. A., Hidayat, B., dan Sunarya, U., 2016, Simulasi dan Analisis Pengenalan Citra Daging Sapi dan Daging Babi dengan Metode GLCM, prosiding SENIATI, pp. 338–343.
  19. Saputra, R., 2016, Implementasi Metode Wavelet Haar Dan Probabilistic Neural Network (Pnn) Untuk Pengenalan Citra Daging babi dan daging sapi, Skripsi thesis, Universitas Islam Negeri Sultan Syarif Kasim Riau, http://repository.uin-suska.ac.id/3062/.
  20. Sutoyo, T., E. Mulyanto, V. Suhartono, O.D. Nurhayati, dan Wijanarto, 2009, Teori Pengolahan Citra Digital, Penerbit ANDI, Yogyakarta,.
  21. Sembiring, R., 2004, Kualitas Daging Babi Dengan Pemberian Zeolit Dan Tepung Darah Sebagai Sumber Protein Dalam Ransum, Media Peternakan, Journal of Animal Science and Technology, vol. 27, no. April, p. 81.