Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal International Journal Software Engineering and Computer Science (IJSECS)
Prayogo, Fadillah Abi
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Automatic Detection of Skin Diseases Using Convolutional Neural Network Algorithms Tundo; Prayogo, Fadillah Abi; Sugiyono
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3021

Abstract

Skin diseases are a major health concern in Indone sia and they can seriously impact a patient’s quality of life. The problem is aggravated by humid tropical climate, limited access to healthcare facilities, and a lack of trained dermatology personnel. The cases in Indonesia are many, and the diagnosis and treatment of skin diseases are delayed, which makes the patient's condition worse. Based on data from the Ministry of Health (Kemenkes), the prevalence of skin disease in Indonesia is 0.62 cases per 10,000 population with the highest prevalence in Eastern Indonesia. Developing a Skin Disease Detection System Based on Convolutional Neural Network (CNN) algorithms. However, CNN algorithms are widely used in image recognition and classification, and can act as an automatic diagnostic system. This system has been developed to aid in diagnosis and improve patient access to dermatological care, especially for remote communities. Users can reach out for services at any time and any location, a practical solution for treating skin health problems. This study's results are anticipated to lower the diagnostic delays and improve the treatment outcomes while offering quick access to reliable dermatological service. This is a great effort on global level for any skin disease supporting to improve life of human lives from skin health issues.
Co-Authors Sugiyono Tundo, Tundo