Pengembangan Aplikasi Mobile Android untuk Deteksi Otomatis Mata Katarak Menggunakan CNN dan Tensorflow

Chotibul Umam Wiranda; Paniran Paniran

doi:10.59581/jkts-widyakarya.v2i3.3722

Authors

Chotibul Umam Wiranda Universitas Mataram
Paniran Paniran Universitas Mataram

DOI:

https://doi.org/10.59581/jkts-widyakarya.v2i3.3722

Keywords:

Mata Katarak, Convolutional Neural Network, Deep Learning, Tensorflow, Android

Abstract

The development of an Android mobile application for automatic cataract detection using Convolutional Neural Network (CNN) and TensorFlow has been conducted. The aim of this research is to provide an easily accessible solution for the public to detect cataracts early, thereby reducing the negative impact of this eye condition. The CNN method is utilized to recognize cataract patterns through image data, with TensorFlow serving as the primary development platform. Preprocessing steps and data processing are implemented to enhance the detection accuracy and address variations in eye images. Evaluation indicates that the application is capable of detecting cataracts with satisfactory accuracy, making it a potential tool for cataract prevention and early management. In conclusion, this application enables rapid and efficient cataract detection, improving the accessibility of eye care and contributing to enhancing overall quality of life for communities by providing early intervention and treatment options.

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