Article Per Year (5 Year)
p-Index From 2020 - 2025
1.686
P-Index
This Author published in this journals
All Journal JIK Jurnal Ilmu Komputer Scientific Journal of Informatics E-Dimas: Jurnal Pengabdian kepada Masyarakat Sinkron : Jurnal dan Penelitian Teknik Informatika JMM (Jurnal Masyarakat Mandiri) JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) KOMPUTA : Jurnal Ilmiah Komputer dan Informatika Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Pilar Teknologi : Jurnal Penelitian Ilmu-ilmu Teknik Jurnal Informatika: Jurnal Pengembangan IT Journal of Applied Informatics Science
Ginanjar Wiro Sasmito, Ginanjar Wiro
Politeknik Harapan Bersama
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Nursing Social Sciences Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Applied Informatics Science

 1 
A Web-Based Chatbot-Integrated Application for Skin Disease Detection Using ResNet50 Architecture Naovi Magfiroh; Sasmito, Ginanjar Wiro; Ilmadina, Hepatika Zidny
Journal of Applied Informatics Science Volume 1 Issue 1 (2025)
Publisher : GWS Group

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The skin is a vital human organ located on the outermost part of the body and is vulnerable to various external stimuli and diseases. The high prevalence of skin diseases in Indonesia indicates a lack of public awareness regarding skin health. This study aims to develop a web-based application capable of detecting 10 types of skin diseases quickly and accurately using the ResNet50 architecture and computer vision technology. The research stages include the creation of a Haar Cascade Classifier, developing an image classification model, model evaluation, chatbot development, system design, implementation, and application testing. The results show that the model achieved an accuracy of 90.10% on the training data and 89.06% on the validation data. The integrated chatbot also provided additional information with a response accuracy of 87.50%. System testing demonstrated good performance based on black-box testing and scored 77.625 on the System Usability Scale (SUS), which falls into the "Good" category. This application can detect early skin disease without requiring direct consultation with a doctor.
Co-Authors Af’idah, Dwi Intan Ardi Susanto Arif Hidayah Dega Surono Wibowo, Dega Surono Dyah Apriliani Erinsyah, Moh. Fiqih Fuad Hadiansah, Fuad Haqqani, Humam Asathin Hepatika Zidny Ilmadina Hidayatullah, Muhammad Fikri Humam, Mohammad Muchamad Sobri Sungkar, Muchamad Sobri Muhammad Fikri Hidayattullah, Muhammad Fikri Naovi Magfiroh Nishom, M Oman Somantri Saputri, Berliani Risqi Dwi Taufiq Abidin, Taufiq Very Kurnia Bakti, Very Kurnia Yustia Hapsari, Yustia