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All Journal Jurnal Buana Informatika
Vani Aulia Pramesti
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Computer Science & IT

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Prediksi Penyakit Batu Ginjal dengan Menerapkan Convolutional Neural Network Waluyo Poetro, Bagus Satrio; Mulyono, Sri; Vani Aulia Pramesti
Jurnal Buana Informatika Vol. 15 No. 2 (2024): Jurnal Buana Informatika, Volume 15, Nomor 02, Oktober 2024
Publisher : Universitas Atma Jaya Yogyakarta

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Abstract

Kidney stones are a health problem that requires intensive treatment. If the disease is not treated quickly, it can lead to impaired kidney function and complications to other organs. Computerized Tomography Scan (CT Scan) with high resolution is used to scan the human body for disease diagnosis. The doctor will explain the diagnosis within a few days or one week. This research aims to create a prediction model for the classification of kidney stone disease through CT Scan images by applying the Convolutional Neural Network (CNN) method of DenseNet-121 architecture and deployment using Streamlit. The results of the model in this study with the application of CNN DenseNet-121 architecture are accuracy 98.18%, precision 96.36%, recall 100%, and F1-score 98.14%.
Co-Authors Poetro, Bagus Satrio Waluyo Sri Mulyono