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All Journal Jurnal Kendali Teknik dan Sains
Chotibul Umam Wiranda
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Computer Science & IT

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Pengembangan Aplikasi Mobile Android untuk Deteksi Otomatis Mata Katarak Menggunakan CNN dan Tensorflow Chotibul Umam Wiranda; Paniran Paniran
Jurnal Kendali Teknik dan Sains Vol. 2 No. 3 (2024): Juli : Jurnal Kendali Teknik dan Sains
Publisher : Universitas Katolik Widya Karya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jkts-widyakarya.v2i3.3722

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.
Co-Authors Paniran Paniran