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All Journal Jurnal Ilmiah Teknologi dan Komputer (JITTER)
Noval Aditya Candra Pratama
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Computer Science & IT

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Implementation of CNN Method with Otsu Thresholding Preprocessing for Pneumonia Detection Surya Afriza; Noval Aditya Candra Pratama; Muhammad Abdul Aziz; Faisal Muttaqin
JITTER: Jurnal Ilmiah Teknologi dan Komputer Vol. 7 No. 1 (2026): JITTER, Vol.7, No.1, April 2026
Publisher : Program Studi Teknologi Informasi, Fakultas Teknik, Universitas Udayana

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Abstract

Pneumonia is a lung infection requiring rapid diagnosis to prevent fatal complications, yet X-ray image quality often hinders manual detection accuracy. This study proposes a hybrid approach using a Convolutional Neural Network (CNN) optimized with Otsu Thresholding for lung area (Region of Interest) segmentation. Experiments were conducted on 1,840 images from a secondary dataset. Evaluation results demonstrate a highly balanced and superior model performance, achieving 96% Recall, 91% F1-Score, and 96% Accuracy. The alignment between accuracy and recall values indicates that the model possesses equally good sensitivity and specificity in detecting both positive and negative cases. These findings prove that Otsu pre-processing effectively assists the CNN in focusing on pathological features, making this method a promising automated diagnostic solution.
Co-Authors Faisal Muttaqin Muhammad Abdul Aziz Surya Afriza