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All Journal Panrita Abdi - Jurnal Pengabdian pada Masyarakat Sinkron : Jurnal dan Penelitian Teknik Informatika Tech-E JRST (Jurnal Riset Sains dan Teknologi) Jurnal Media Elektro : Journal of Electrical Power, Informatics, Telecommunication, Electronics, Computer and Control System Journal of Informatics and Communication Technology (JICT)
Arif Rahman Hakim
Universitas Medika Suherman
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Mathematics Other

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Journal : Sinkron : Jurnal dan Penelitian Teknik Informatika

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Android-Based Herpes Disease Detection Application using Image Processing Arif Rahman Hakim; Dewi Marini Umi Atmaja; Tugiman Tugiman; Amat Basri
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2023): Articles Research Volume 8 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.11913

Abstract

Herpes is a viral infection that causes a skin disease that is widespread throughout the world. Herpes virus is a DNA virus transmitted via infected skin, saliva, and other body fluids. Herpes is characterized by chickenpox-like nodules in one area of the skin, swollen tissue surrounding the nodule, and blister formation on the nodule. Digital image processing that can detect herpes disease is anticipated to reduce physical contact between physicians and patients during skin disease diagnosis. This study's methodology includes collecting data on herpes disease, developing machine-learning models using the CNN algorithm, and deploying the model as an Android application. This study makes use of actual data collected via smartphones, Pocket Cameras, and internet-sourced photographs. The data include 12,645 images of skin affected by herpes and normal skin. Using 100 epochs and the Adadelta optimizer, the accuracy of this study is 85 percent.
Co-Authors Amat Basri Amat Basri Amat Basri Andri Ariyanto Deny Haryadi Dewi Marini Umi Atmaja Dewi Marini Umi Atmaja Dewi Marini Umi Atmaja Muhamad Syafii Risma Adisty Nilasari Tugiman Tugiman