Fakultas Teknologi Informasi

Artificial intelligence detection of refractive eye diseases using certainty factor and image processing

Penulis
Dosen:
  1. HENDI SUHENDI
  2. RIZAL RACHMAN
  3. SARI SUSANTI
Mahasiswa:
  1. Adi Karawinata Satyanegara
Tanggal Terbit
02 Desember 2024
Kategori
Jurnal Internasional Bereputasi [Q3]
Penerbit
Indonesian Journal of Electrical Engineering and Computer Science
Kota / Negara
Yogyakarta / Indonesia
Volume
36
Halaman
1787
ISSN
2502-4752
E-ISSN
2502-4760
DOI
10.11591/ijeecs.v36.i3.pp1787-1797
URL
https://ijeecs.iaescore.com/index.php/IJEECS/article/view/39275
Abstrak
Refractive errors are defined as an impairment in the eye’s capacity to focus
light, resulting in the formation of blurred or unfocused images. These issues
arise from alterations in the shape of the cornea, the length of the eyeball, or
the aging of the crystalline lens. It is anticipated that the prevalence of visual
impairment will increase in conjunction with global population growth. At
present, a significant number of countries have not yet accorded sufficient
priority to eye health within their healthcare systems. This has resulted in
insufficient awareness and reluctance to seek costly specialized care. This
study proposes the development of an advanced refractive eye disease
detection system with the objective of improving diagnostic accuracy,
disseminating disease information, and reducing financial barriers to
specialist consultation. The research employs certainty factor (CF) methods
and image processing with feature extraction. The initial results demonstrate
the potential for identifying specific refractive eye diseases with high
certainty through the analysis of symptoms and the examination of
photographs of the eye. The proposed approach provides an alternative
method for diagnosing refractive eye diseases, which could enhance access
to refractive eye care services and reduce the economic burden on patients.