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All Journal Jurnal Ilmiah Sains dan Teknologi
Kusuma, Daniel
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Computer Science & IT Decision Sciences, Operations Research & Management Library & Information Science Physics

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Klasifikasi Penyakit Paru-Paru Dengan Citra X-Ray Menggunakan Metode Convolutional Neural Network Kusuma, Daniel; Rarasati, Dionisia Bhisetya
Jurnal Ilmiah Sains dan Teknologi Vol. 9 No. 2 (2025): Jurnal Ilmiah Sains dan Teknologi
Publisher : Teknik Informatika Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5555/23mj8c35

Abstract

This research explores the utilization of Convolutional Neural Network (CNN) methods to classify lung diseases, including COVID-19, Tuberculosis, and Pneumonia. The focus is on developing a CNN model for lung disease classification using a dataset that has undergone augmentation. Data augmentation is performed through various transformations such as rotation, horizontal_flip, vertical_flip, shear_range, and zoom_range. The dataset is divided into 70% for training, 20% for validation, and 10% for testing, totaling 2200 data points. The results indicate that the constructed model successfully achieved an accuracy of 96.49% in the training process and 95% on the testing data. This research demonstrates the potential of CNN in classifying lung diseases quite effectively after model training.
Co-Authors Rarasati, Dionisia Bhisetya