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Anggita Nurfadilla Mahardika
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Diagnosis Penyakit Mata menggunakan Metode Improved K-Nearest Neighbor Anggita Nurfadilla Mahardika; Agus Wahyu Widodo; Muh. Arif Rahman
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The eye has a very important for the human body which is as the sense of sight. Humans can do a variety of activities based on visual information received through the eyes. A healthy eye is very supportive to various activities and make out activities without obstacles. So the importance of the part of the eye, health of eye needs to be right considered and cared because the eyes do not escape the threat of disease that can disturb with vision. But, in the fact the people is still underestimate and consider the problem of eye disease is not dangerous. Lack of public awareness about eye diseases can worsen eye conditions if that cannot be handled and resolved to quickly. Beside, the factors that make some people still apathetic to eye diseases, they do not know if they suffer from eye disease and ignore the symptoms that are felt. Public ignorance of the symptoms that arise due to eye disease because people are still reluctant to check eye health to health services, because the cost of the examination, especially for the cost of specialist doctors that are considered quite high. Therefore, in this problem the authors then build an early diagnosis of eye diseases to facilitate the public in recognizing visual disturbances or eye diseases based on symptoms that are felt. In construction this system, the writer uses the Improved K-Nearest Neighbor methods. The improved K-Nearest Neighbor method has been proven to get a good results. The highest accuracy from system using lmproved K-Nearest Neighbor method by 88% in the process of diagnosis of eye disease.
Co-Authors Agus Wahyu Widodo Muh. Arif Rahman