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Application of the Support Vector Machine (SVM) Algorithm for the Diagnosis of Diabetic Retinopathy

Authors

  • Yuliadi Universitas Teknologi Informasi
  • Fadhli Dzil Ikram Universitas Teknologi Sumbawa
  • M. Julkarnain Universitas Teknologi Sumbawa
  • Fahri Hamdan Universitas Teknologi Sumbawa
  • Halid Nuryadi Universitas Teknologi Sumbawa

DOI:

10.47709/brilliance.v3i2.3436

Keywords:

Diabetic Retinopathy, MATLAB, GLCM, SVM, Human Error

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Abstract

Diabetic Retinopathy (DR) is a disease whose main cause is complications of diabetes mellitus. High levels of sugar in the blood (glucose) are caused by the pancreas' inability to produce insulin. Prevention of diabetic retinopathy and blindness by carrying out examinations at an early stage and doing them regularly. Currently, doctors still carry out examinations manually so they are prone to errors in examinations. This research aims to build an application to diagnose Diabetic Retinopathy in order to facilitate the work of the medical team and doctors at the eye clinic. In the application creation process, MATLAB is used, while feature extraction uses GLCM and for classification, SVM is used. The results of the research are that doctors and medical teams are helped in carrying out manual patient diagnoses and reduce the occurrence of human error.

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ARTICLE Published HISTORY

Submitted Date: 2024-01-12
Accepted Date: 2024-01-13
Published Date: 2024-01-18

How to Cite

Yuliadi, Dzil Ikram, F., Julkarnain, M., Hamdan, F. ., & Nuryadi, H. (2024). Application of the Support Vector Machine (SVM) Algorithm for the Diagnosis of Diabetic Retinopathy. Brilliance: Research of Artificial Intelligence, 3(2), 416-422. https://doi.org/10.47709/brilliance.v3i2.3436

Issue

Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023

Section

Articles

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Copyright (c) 2023 Yuliadi; Fadhli Dzil Ikram, M. Julkarnain, Fahri Hamdan, Halid Nuryadi

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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