Irawan, Irawan (2014) Klasifikasi fitur diabetic retinopathy menggunakan learning vector quantization (LVQ). Undergraduate thesis, Universitas Islam Negeri Maulana Malik Ibrahim.
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Abstract
INDONESIA:
Salah satu dampak dari penyakit Diabetic Mellitus(DM) adalah penyumbatan pembuluh darah mata, dikenal sebagai penyakit Diabetic Retinopathy (DR). Gejala yang dapat ditemui oleh orang yang terkena penyakit ini adalah kesulitan dalam membaca, penglihatan kabur, penglihatan tiba-tiba menurun pada satu mata, melihat lingkaran-lingkaran cahaya, melihat bintik gelap, dan cahaya berkedip. Hal ini terjadi karena ada rembesan darah yang mengenai lensa mata.
Penelitian dilakukan untuk membuat suatu aplikasi yang dapat menampilkan hasil klasifikasi Diabetic Retinopathy sesuai dengan tingkat stadiumnya yaitu normal, Mild Non-Proliferate Diabetic Retinopathy (Mild NPDR), Moderate Non-Proliferate Diabetic Retinopathy (Moderate NPDR) dan Proliferate Diabetic Retinopathy (PDR).Penelitian ini menggunakan pengolahan citra digital dengan metode Learning Vector Quantization (LVQ) untuk mengklasifikasi ciri.
Hasil pengujian aplikasi menunjukkan bahwa tingkat keakurasian metode Learning Vector Quantization (LVQ) dalam mengklasifikasi DR berdasarkan tingkatannya, normal, MildNPDR, Moderate NPDR dan PDR mencapai 96 %.
ENGLISH:
One of the effects of the Diabetic Mellitus (DM) disease is a blockage of eye blood vessels, known as the Diabetic retinopathy (DR) disease. Symptoms that can be encountered by people affected by this disease are difficulty in reading, blurred vision, sudden decreased vision in one eye, seeing halos, seeing dark spots, and a flashing light. This happens because there is seepage of blood on the lens of the eye.
The research was conducted to create an application that can display the results of the classification diabetic retinopathy according to the stage that is normal, Mild Non-Proliferate Diabetic Retinopathy (Mild NPDR), Moderate Non-Proliferate Diabetic Retinopathy (Moderate NPDR), and Proliferate Diabetic Retinopathy (PDR). The research use digital image processing to clasifiy the features by Learning Vector Quantization (LVQ) method.
The application test results shows that level accuracy of Learning Vector Quantization (LVQ) method in classify the DR based levels, normal, MildNPDR, Moderate NPDR dan PDR getting to 96%.
Item Type: | Thesis (Undergraduate) | |||||||||
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Supervisor: | Faisal, Muhammad and Kusumawati, Ririen | |||||||||
Contributors: |
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Keywords: | Diabetic Retinopathy; Learning Vector Quantization (LVQ) | |||||||||
Departement: | Fakultas Sains dan Teknologi > Jurusan Teknik Informatika | |||||||||
Depositing User: | Dian Anesti | |||||||||
Date Deposited: | 13 Oct 2017 14:07 | |||||||||
Last Modified: | 13 Oct 2017 14:07 | |||||||||
URI: | http://etheses.uin-malang.ac.id/id/eprint/8054 |
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