Please use this identifier to cite or link to this item:
https://repository.unej.ac.id/xmlui/handle/123456789/111382
Title: | Pengembangan Aplikasi Menggunakan Metode Convolutional Neural Network dengan Arsitektur VGG-16 untuk Identifikasi Penyakit Paru |
Authors: | NEGORO, Verdy Bangkit Yudho |
Keywords: | Convolutional Neural Network Tuberkulosis Pneumonia Covid-19 VGG-16 |
Issue Date: | 16-Nov-2022 |
Publisher: | Fakultas Ilmu Komputer |
Abstract: | The rate of lung problems around the world continues to increase. According to WHO, different lung diseases including pneumonia, tuberculosis, and Covid-19 disease, the characteristics of these two diseases are almost the same [1]. The cause of death of people with lung disease during the Covid- 19 pandemic is due to the lengthy diagnosis process. Other factors, such as X-ray imaging results, often appear fuzzy and lack contracture, so an image seen by multiple observers can make different diagnoses. The study will classify lung images into four categories: normal lungs, tuberculosis, pneumonia, and Covid-19. The method chosen by the researcher is a Constitutive Neural Network using the VGG-16 architecture. The test results show that the Convolutional Neural Network (CNN) model gets the test results on the model having the highest accuracy in the scenario without using a pre-trained model by using a data comparison of 9:1 at epoch 50, with an accuracy of 94%, while the lowest result is in the scenario test data 8:2 epoch 50 at non-pre- trained model with an accuracy of 87%. |
URI: | https://repository.unej.ac.id/xmlui/handle/123456789/111382 |
Appears in Collections: | UT-Faculty of Computer Science |
Files in This Item:
File | Description | Size | Format | |
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TUGAS AKHIR.pdf Until 2027-12-30 | 3.21 MB | Adobe PDF | View/Open Request a copy |
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