Maretta Bunga Adhiena Santoso, . (2020) Klasifikasi Telur Ayam Omega-3 Menggunakan Metode Support Vector Machine. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Eggs are livestock products that can help people get enough nutrients. Eggs contain nutrients that are easily digestible by humans. In Indonesia, chicken eggs are the most desirable food ingredients, besides being easily found and reasonably priced. Chicken eggs have a variety of types, ranging from the eggs of the country chickens, eggs of the village, organic chicken eggs. Compared to the other eggs, the omega-3 chicken eggs are one of the eggs that have a price far above the average egg in general. But the omega-3 chicken eggs have more efficacy. During this way distinguish chicken eggs and omega-3 chicken eggs can be known through the egg yolks. If done the egg breakdown, which contains omega-3 will be visible color differences. Reddish color is seen in the egg yolks omega-3 while the egg yolks on the chicken eggs are yellow. So, the detection of the omega-3 chicken eggs without making a solution to the cage first, so as to classify the type of omega-3 chicken eggs with the chicken eggs using GLCM method to extract the characteristics of texture, after known differences characteristic texture, then done classification with Support vector Machine (SVM) method. The expected outcome is to give the classifying omega-3 chicken eggs with the chicken eggs with high accuracy. However, this study resulted in an accuracy of 67.30%.
Item Type: | Thesis (Skripsi) |
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Additional Information: | [No. Panggil : 1610511017] [Pembimbing 1 : Didit Widiyanto] [Pembimbing 2 : Artambo B. Pangaribuan] [Penguji 1 : Ermatita] [Penguji 2 : Bambang Tri Wahyono] |
Uncontrolled Keywords: | Classification, omega-3 chicken eggs, SVM, Support vector Machine, GLCM |
Subjects: | Q Science > QH Natural history > QH301 Biology |
Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
Depositing User: | Maretta Bunga Adhiena |
Date Deposited: | 12 Jan 2022 05:17 |
Last Modified: | 12 Jan 2022 05:17 |
URI: | http://repository.upnvj.ac.id/id/eprint/6846 |
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