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Abstract

According to the World Health Organization (WHO), Tuberculosis and Pneumonia are two of the 10 biggest causes of death in the world. To reduce the risk of contracting both diseases, early and accurate diagnosis is needed. One way to achieve early and accurate diagnosis is to integrate image processing into the diagnosis process. The aim of this research is to test the CNN Inception V3 algorithm in identifying a case of Tuberculosis and Pneumonia disease by using a photo of electromagnetic radiation from a person's body wavelength. From the photos, the results obtained were the percentage of accuracy of x-ray photos of normal lungs is 99.63%, the percentage of accuracy of x-ray photos of tuberculosis lungs is 99.82% and the percentage of accuracy of x-ray photos of lungs with pneumonia is 99.69%.

Keywords

CNN Inception V3 Lungs Pneumonia Tuberculosis

Article Details

How to Cite
Kosman, A. W., Wahyuningsih, Y., & Mahendrasusila, F. (2024). Pengujian Algoritma Inception V3 dalam Mengidentifikasi Penyakit Tuberculosis dan Pneumonia. Jurnal Teknik Informatika Dan Komputer, 3(1), 26–30. https://doi.org/10.22236/jutikom.v3i1.13879
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