Krisna Putra, Guntur (2015) KLASIFIKASI DAGING HEWAN FITUR CITRA DIGITAL MENGGUNAKAN SVM (SUPPORT VECTOR MACHINE). S1 thesis, Universitas Sultan Ageng Tirtayasa.
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KLASIFIKASI DAGING HEWAN FITUR CITRA DIGITAL.pdf - Published Version Restricted to Registered users only until 2015. Download (4MB) |
Abstract
Some action mixing beef with pork in the market –traditional market. This can be detrimental to the consumer what's harming the Mosloems are prohibited from eating pork. This research aims to classify the type of pork and beef in a digital image.There are two types of data in this study i.e. training data and test data which consists of RGB images. This research was conducted on pre-process by changing the RGB image on both the type of the data with a grayscale image and then extraction properties by using the properties of the order of one and a half. Parameters on the order of one is the mean, variance, skewness and the order of the two is the contrast, correlation, variance of grayscale histogram. the classification of types of meat into two classes using Support Vector Machine (SVM) with application of WEKA (Waikato Environtment for Knowledge Analysis) version 3.7.10. Accuracy of results from each test type of pork and beef such as evaluation on training set: 81,111%, evaluation on testing sets of :90%, cross-validation folds 2: 81,111%, cross-validation folds 3: 78,8889%, cross- validation 4: 78,8889% . Keywords : porks,beef ,histogram, SVM
| Item Type: | Thesis (S1) | |||||||||
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| Additional Information: | Beberapa tindakan pencampuran daging sapi dengan daging babi di pasar – pasar tradisonal. Hal ini dapat merugikan konsumen terlebih merugikan masyarakat muslim yang dilarang mengkonsumsi daging babi. Penelitian ini bertujuan untuk mengklasifikasi jenis daging babi dan daging sapi pada citra digital. Terdapat dua jenis data pada penelitian ini yaitu data latih dan data uji yang berupa gambar RGB (Red, Green, Blue) . Pada penelitian ini dilakukan pra proses dengan mengubah citra RGB pada kedua jenis data tersebut dengan citra grayscale yang kemudian diekstrasi ciri dengan menggunakan orde satu dan orde dua. Parameter – parameter pada orde satu adalah mean, variance, skewness dan orde dua adalah contrast, correlation, variance dari histogram grayscale. Kemudian klasifikasi jenis daging ke dalam dua kelas menggunakan SVM (Support Vector Machine) dengan aplikasi WEKA (Waikato Environtment for Knowledge Analysis) version 3.7.10. Hasil keakurasian dari tiap pengujian jenis daging babi dan daging sapi diantarnya evaluation on training set 81,111%, evaluation on testing set 90%, cross-validation folds 2 81,111%, cross-validation folds 3 78,8889%, cross- validation folds 4 78,8889%. Kata Kunci : Daging babi , daging sapi, histogram, SVM, | |||||||||
| Uncontrolled Keywords: | Kata Kunci : Daging babi , daging sapi, histogram, SVM, Keywords : porks,beef ,histogram, SVM. | |||||||||
| Subjects: | T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | 03-Fakultas Teknik 03-Fakultas Teknik > 20201-Jurusan Teknik Elektro |
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| Depositing User: | Perpustakaan Pusat | |||||||||
| Date Deposited: | 03 Dec 2021 13:50 | |||||||||
| Last Modified: | 03 Dec 2021 13:50 | |||||||||
| URI: | http://eprints.untirta.ac.id/id/eprint/9376 |
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