Jurnal Computer Science and Information Technology (CoSciTech)
Vol 4 No 3 (2023): Jurnal Computer Science and Information Technology (CoSciTech)

Deep Learning untuk mendeteksi gangguan lambung melalui citra iris mata

Mukhtar, Harun (Unknown)
Baidarus (Unknown)
Aryanto, Eggy (Unknown)
Saputra Sy, Yandiko (Unknown)



Article Info

Publish Date
29 Dec 2023

Abstract

The stomach is one of the essential organs of the human digestive system. If the stomach organ cannot work typically, it will cause problems. This is a disease that occurs in the stomach organs. Gastric disease also occurs due to a lack of knowledge about stomach disease, so people ignore the symptoms that arise. Gastric disease is a disease that is considered very serious. If left alone, it can cause other diseases to occur. Generally, finding out the presence of stomach disease is still done manually, and several tests are carried out when stomach disease has recurred. Gastric disorders were classified using 360 iris images taken manually via a digital camera and a web database of iris images. The author used the Radial Basis Function Neural Network (RBFNN) method to classify iris images of patients with gastric disorders in this study. The results obtained from this research can organize the iris images of people with gastric disturbances. Classification of iris images of patients with gastric disorders achieved a training accuracy rate of 65.00%.

Copyrights © 2023






Journal Info

Abbrev

coscitech

Publisher

Subject

Computer Science & IT

Description

Jurnal CoSciTech (Computer Science and Information Technology) merupakan jurnal peer-review yang diterbitkan oleh Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Univeritas Muhammadiyah Riau (UMRI) sejak April tahun 2020. Jurnal CoSciTech terdaftar pada PDII LIPI dengan Nomor ISSN ...