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Entra Betlin Ladauw
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Identifikasi Penyakit Mata Menggunakan Metode Learning Vector Quantization (LVQ) Entra Betlin Ladauw; Dian Eka Ratnawati; Ahmad Afif Supianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Taking care and maintaining healthy eyes are very important for human, because eyes are one of the senses that help human to do daily activities. Eyes that give visual information to human, cannot be separated from the threat of many eyes diseases. The diseases can attack from small to big scale. Unfortunately, eyes diseases are usually considered not to have such potential to harm human, so eyes health often to be ignored by people in general. Therefore, in this paper a system to identify eyes diseases has been developed using Learning Vector Quantization (LVQ) method. This method can give classification to a pattern that represent specific class, which will move to a nearer position to corresponding class when the classification data point is true. In this research, there are 21 symptoms and 9 eyes diseases that processed in training and testing processes, where the data were divided into training data and testing data. In training process, LVQ method did some stages to get final weight. The weight will be used in testing process. Using LVQ method, obtained parameter values are α = 0.4, Dec α = 0.8, Min α = 0.00001, Max Epoch = 25, training data = 100 data (80%) and data test = 25 data (20%). From accuracy testing for this system, the result show 82.80% average accuracy and 92% highest accuracy, that means this system works fine. So, it can be concluded that LVQ method can be used for eyes diseases identification.
Co-Authors Ahmad Afif Supianto Dian Eka Ratnawati