DETEKSI PENYAKIT COVID-19 PADA CITRA RONTGENT THORAX MENGGUNAKAN BACKPROPAGATION

Fredy Aryo Saputro, . (2021) DETEKSI PENYAKIT COVID-19 PADA CITRA RONTGENT THORAX MENGGUNAKAN BACKPROPAGATION. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

[img] Text
AWAL.pdf

Download (1MB)
[img] Text
ABSTRAK.pdf

Download (151kB)
[img] Text
BAB 1.pdf

Download (46kB)
[img] Text
BAB 2.pdf

Download (270kB)
[img] Text
BAB 3.pdf

Download (151kB)
[img] Text
BAB 4.pdf

Download (412kB)
[img] Text
BAB 5.pdf

Download (31kB)
[img] Text
Daftar Pustaka.pdf

Download (35kB)
[img] Text
DAFTAR RIWAYAT HIDUP.pdf

Download (266kB)
[img] Text
LAMPIRAN.pdf

Download (257kB)

Abstract

The pandemic of the spread of the Covid-19 virus that has occurred throughout the world has overwhelmed many countries, including Indonesia. With this incident, the medical personnel will have to work harder in this viral environment. Examination of this virus using the PCR method and the Rapid Test takes time to get the results of the examination. The increasing number of patients simultaneously experiencing these symptoms makes it difficult and makes treatment time by medical personnel longer. In addition to PCR and Rapid Test, the supporting methods for examining this disease are the chest x-ray where the lungs of the unexpected patient who are exposed to the virus can be seen from the X-ray and shorten the suspicion that the patient is exposed so that immediate treatment can be done based on the results of the chest X-ray. The use of backpropagation where later you will wait for abnormalities from unhealthy and sick photos. The hope is that the use of backpropagation will make it easier for medical personnel, lighten the workload, and shorten the time for further treatment based on chest x�rays from patients in the ER.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 1410511062] [Pembimbing 1: Yuni Widiastiwi] [Pembimbing 2: Mayanda Mega Santoni] [Penguji 1: Iin Ernawati] [Penguji 2: Ati Zaidiah]
Uncontrolled Keywords: Covid 19, Rontgent Thorax, Backpropagation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Fredy Aryo Saputro
Date Deposited: 02 Jun 2022 00:26
Last Modified: 02 Jun 2022 00:26
URI: http://repository.upnvj.ac.id/id/eprint/17829

Actions (login required)

View Item View Item