Skripsi

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

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Penilaian

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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%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407006669	T160406	T1604062024	Central Library (REFERENCE)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1604062024

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xv, 42 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

616.248 07

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Teknik Informatika
Pneumonia – Diagnosis – Gambar Sinar-X

Specific Detail Info

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Statement of Responsibility

TUTI

Other version/related

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