Khasanah, Khalimatul and Irianto, Suhendro Yusuf (2025) Implementasi Thresholding Dalam Mendiagnosa Penyakit Asam Lambung Dengan Metode Sobel Menggunakan Citra Rontgen. Skripsi thesis, Institut Informatika dan Bisnis Darmajaya.
![[img]](http://repo.darmajaya.ac.id/style/images/fileicons/text.png) |
Text
cover.pdf Download (18kB) |
|
Text
ABSTRAK.pdf Download (29kB) |
|
Text
persetujuan pengesahan.pdf Download (1MB) |
|
Text
DAFTAR ISI.pdf Download (107kB) |
|
Text
BAB I.pdf Download (53kB) |
|
Text
bab II.pdf Download (550kB) |
|
Text
BAB III.pdf Download (408kB) |
|
Text
BAB IV.pdf Download (506kB) |
|
Text
BAB V.pdf Download (36kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (73kB) |
|
Text
lampiran1.pdf Download (132kB) |
Abstract
The definition of stomach acid disease or gastroesophageal reflux disease (GERD) is the appearance of a burning feeling in the chest due to stomach acid rising into the esophagus. Symptoms of stomach acid appear at least twice a week. The main symptom of increased stomach acid is a burning feeling in the chest (heartburn). These symptoms can be accompanied by complaints of other digestive disorders, such as frequent belching, nausea and vomiting, and shortness of breath. The results of x-ray images often appear blurry, lack contrast, and so on, so that one image observed by several observers can produce different readings. Based on the image segmentation results and calculating the number of white pixels, the image will identify whether cells are identified as gastric disease or not. In determining identification, the reference is the number of white pixels. If the number of white pixels is greater than or equal to the reference image then the cell is said to be healthy/the condition of the stomach is fine and conversely if the number of white pixels is smaller than the reference image then the cell is said to be sick/there is a problem with the stomach. This system can identify stomach diseases by comparing problematic stomach acid levels with healthy stomach acid using a segmentation method and calculating the number of image pixels between healthy images and diseased images.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Subjects: | Ilmu Komputer eSkripsi |
| Divisions: | Skripsi/TA & PKPM/KP - Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | khalimatul khasanah aleena |
| Date Deposited: | 03 Feb 2025 01:07 |
| Last Modified: | 03 Feb 2025 01:07 |
| URI: | http://repo.darmajaya.ac.id/id/eprint/19387 |
Actions (login required)
 |
View Item |