Support vector machine for omega 3 classification based on histogram equalization. (March 2019)

• Record Type: Journal Article
• Authors: Liantoni, Febri; Adi Santoso, Agus; Soebandhi, Santirianingrum; Sagala, Danner; Tritias Utami, Rosanita; Freedom Nanuru, Ricardo; Asfar, Muhammad; kristianto, sonny; Hardi, ; Trianton, Teguh; Wikansari, Rinandita; Indriyani Achmad, Listian; Utami Sutiksno, Dian; Fatimah, ; Hidayat, Rahmat; Youhanita, Ety; Laksitarahmi Isrianto, Pramita; Maya Sari Siswi Ciptaningsih, Eka; Zuliana, Eka; Sallu, Sulfikar; Chairuddin, ; Fajar Budi Hartanto, Cahya; Fathimah, ; Andayani, Dahlia; Rosaliza, Mita; Hendrawan, Aria; Rustam, ; Dian Angriani, Andi; Wahyuni, Sri; Arjulanaya,
• Is Part Of: Journal of physics. Volume 1175(2019)
• Publication Date: 2019-03
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1175/1/012113
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Eggs are one of the animal food ingredients consumed in addition to meat, fish, and milk. But now the engineered eggs have emerged that have a higher nutritional value, namely eggs that contain omega-3. The distinguishing part is omega-3 egg yolks rather yellow while ordinary egg yolks are more reddish. The purpose of this research was to classify eggs based on texture using the support vector machine method. To find out the value of egg texture using extraction of first-order statistical features. Based on the results of the testing of this research obtained an accuracy rate of 88.75% based on 120 training data and 80 test data.