Muh. Ahyan Saputra, . (2023) PERANCANGAN SISTEM PREDIKSI PENYAKIT PARU-PARU (TORAX) BERBASIS WEBSITE. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
In identifying pneumonia, medical images such as X-rays are needed to make it easier to recognize the characteristics of the disease. Although the condition of lung inflammation can be seen easily through X-rays, the quality of the resulting images is not always good, and they tend to be vague and have similarities between other types of lung diseases. To reduce errors in diagnosing lung diseases, several previous studies have developed a system to identify pneumonia, covid-19, Tuberculosis, infiltration, atelectasis and pleural effusion. The system developed uses machine learning technology using Convolutional Neural Network (CNN). Similarly, this research focuses on identifying lung pneumonia, covid-19, Tuberculosis, infiltration, atelectasis and pleural effusion with the Website-based CNN algorithm. The system development method used is the waterfall method. The expected final result is that the system can identify normal lungs and pneumonia lungs with an accuracy rate of more than 98%.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 1910512087] [Pembimbing: Rio Wirawan] [Penguji 1: Rudhy Ho Purabaya] [Penguji 2: Ati Zaidiah] |
| Uncontrolled Keywords: | pneumonia, covid-19, Tuberculosis, infiltration, atelectasis and pleural effusion |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software Q Science > QH Natural history > QH301 Biology Q Science > QM Human anatomy |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1) |
| Depositing User: | Muh. Ahyan Saputra |
| Date Deposited: | 20 Feb 2023 06:56 |
| Last Modified: | 20 Feb 2023 06:56 |
| URI: | http://repository.upnvj.ac.id/id/eprint/22886 |
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