Riman, Gugi Walus (2025) PREDIKSI KANDUNGAN PROTEIN KUNING TELUR PIGMEN LUTEIN DAN XANTOFIL MENGGUNAKAN BACKPROPAGATION NEURAL NETWOK BERBASIS FITUR WARNA. Skripsi (Bachelor) thesis, Universitas Muhammadiyah Bengkulu.
![[img]](http://repository.umb.ac.id/style/images/fileicons/text.png) |
Text (Fulltext)
Gugi Walus Riman_2155201215_full text.pdf - Submitted Version Restricted to Repository staff only Download (3MB) | Request a copy |
|
Text (Turnitin)
GUGI WALUS RIMAN SKRIPSI TI ASC1_11zon.pdf - Submitted Version Restricted to Repository staff only Download (1MB) | Request a copy |
|
Text (ABSTRAK + BAB 1)
Gugi Walus Riman_2155201215_abstrak+bab 1.pdf - Submitted Version Download (2MB) |
|
Text (BAB 2)
Gugi Walus Riman_2155201215_bab 2.pdf - Submitted Version Download (417kB) |
|
Text (BAB 3)
Gugi Walus Riman_2155201215_bab 3.pdf - Submitted Version Restricted to Repository staff only Download (337kB) | Request a copy |
|
Text (BAB 4)
Gugi Walus Riman_2155201215_bab 4.pdf - Submitted Version Restricted to Repository staff only Download (1MB) | Request a copy |
|
Text (BAB 5)
Gugi Walus Riman_2155201215_bab 5.pdf - Submitted Version Download (195kB) |
|
Text (Ref + Lamp)
Gugi Walus Riman_2155201215_ref+lamp.pdf - Submitted Version Download (241kB) |
Abstract
Egg yolk is one of the important protein sources and contains other nutrients such as lutein and xanthophyll. Currently, protein content testing is usually conducted using laboratory methods such as Kjeldahl, Biuret, or spectrophotometry. Although accurate, these methods require high costs, long processing time, are destructive to samples, and require expert personnel. Therefore, an alternative method that is faster, cheaper, and non-destructive is needed. This research aims to develop a prediction system for egg yolk protein content using Backpropagation Neural Network (BNN) method based on color feature extraction. Data was collected by photographing egg yolks using a digital camera under controlled lighting conditions. The obtained images were converted from RGB to HSV color model, then analyzed for protein content using an application developed with Python programming language. The research results show that protein content in egg yolks varies. From 40 egg yolk images, the highest protein content was found in free-range chicken eggs, followed by commercial chicken eggs, omega chicken eggs, and duck eggs. The Backpropagation Neural Network (BNN) method achieved accuracy of up to 85% for protein prediction, 78% for lutein, and 82% for xanthophyll. These results indicate that this approach can be an effective alternative to replace expensive and time-consuming chemical analysis methods
| Item Type: | Thesis (Skripsi (Bachelor)) |
|---|---|
| Additional Information: | Dosen Pembimbing : Rozali Toyib, S.kom, M, Kom |
| Uncontrolled Keywords: | Egg Yolk, Color Feature Extraction, Protein, BNN |
| Subjects: | Universitas Muhammadiyah Bengkulu > 02-Fakultas Teknik > 55201-(S1) Teknik Informatika 02-Fakultas Teknik > 55201-(S1) Teknik Informatika |
| Divisions: | 02-Fakultas Teknik > 55201-(S1) Teknik Informatika Subjek Terkait > 02-Fakultas Teknik > 55201-(S1) Teknik Informatika |
| Depositing User: | Mrs Hildayani Hildayani |
| Date Deposited: | 22 Sep 2025 01:23 |
| Last Modified: | 22 Sep 2025 01:23 |
| URI: | http://repository.umb.ac.id/id/eprint/2082 |
Actions (login required)
 |
View Item |