KLASIFIKASI PARU-PARU NORMAL DAN PNEUMONIA PADA CITRA X-RAY MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK DENGAN VGG19

FARAUK, ABDULLAH and Yusliani, Novi and Rizqie, Qurhanul (2024) KLASIFIKASI PARU-PARU NORMAL DAN PNEUMONIA PADA CITRA X-RAY MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK DENGAN VGG19. Undergraduate thesis, Sriwijaya University.

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Abstract

Pneumonia is a lung infection characterized by symptoms such as fever, shortness of breath, and bloody cough. According to data from the World Health Organization (WHO), it is reported that 740,180 children worldwide have lost their lives due to pneumonia, making it a disease that must be promptly addressed and treated. In this study, the authors developed an application to classify normal and pneumonia-affected lungs using the Convolutional Neural Network (CNN) method with VGG19 on a web-based application. The data used in the study consisted of 5,840 images, with a training data ratio of 90% and a testing data ratio of 10%. This research involves two models: the first model is more complex without regularization techniques, while the second model employs regularization techniques. The first model resulted in an accuracy of 91.83%, precision of 91.04%, recall of 96.41%, and an f1-score of 93.65%. Meanwhile, the second model yielded an accuracy of 91.19%, precision of 89.79%, recall of 96.92%, and an f1-score of 93.22%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Ilmu Komputer, Pembelajaran Mesin
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Abdullah Farauk
Date Deposited:	16 Dec 2024 05:28
Last Modified:	16 Dec 2024 05:28
URI:	http://repository.unsri.ac.id/id/eprint/160406

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