Annisa Refalinanda Putri, . (2024) PENERAPAN ARSITEKTUR INCEPTIONV3 PADA ALGORITMA CNN UNTUK KLASIFIKASI PNEUMONIA MELALUI ANALISIS CITRA XRAY. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Based on the 2021 report by the United Nations Children’s Fund (UNICEF), pneumonia has become the leading cause of death among diseases. Pneumonia is a lung disease characterized by inflammation caused by an infection from certain microorganisms, one of which is a virus. Viral pneumonia and COVID-19 are types of pneumonia caused by viruses. These two diseases can be distinguished through x-ray image analysis, but they are very similar, requiring a considerable amount of time for expert doctors to differentiate them. Therefore, a system model capable of automatically classifying pneumonia is needed. This study developed a model to classify lung conditions based on x-ray images using a Convolutional Neural Network (CNN) architecture called InceptionV3. The model development was divided into several stages: the first stage involved data collection, the second stage involved data preprocessing, and the third stage involved training the model using two data split ratios, 70:20:10 and 80:10:10, and two different optimizers, Adam and RmsProp. From all the experiments, the best accuracy was achieved with a data split ratio of 80:10:10 using the RmsProp optimizer. The final result of this study achieved an accuracy of 98.49%, and the model was implemented into a web-based application.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2010511099] [Pembimbing: Indra Permana Solihin] [Penguji 1: Widya Cholil] [Penguji 2: Novi Trisman Hadi] |
| Uncontrolled Keywords: | Pneumonia, Lung Disease, X-ray Image, InceptionV3, Convolutional Neural Network (CNN). |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software Q Science > QR Microbiology Q Science > QR Microbiology > QR355 Virology T Technology > TJ Mechanical engineering and machinery |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | ANNISA REFALINANDA PUTRI |
| Date Deposited: | 29 Jul 2024 14:09 |
| Last Modified: | 29 Jul 2024 14:09 |
| URI: | http://repository.upnvj.ac.id/id/eprint/31551 |
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