Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal IKRA-ITH Informatika : Jurnal Komputer dan Informatika
Vardhana, Aryo Romadhon
Unknown Affiliation
Computer Science & IT

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

Found 1 Documents
Search

 1 
Rancang Bangun Aplikasi Berbasis Web Untuk Sistem Deteksi Penyakit Malaria Menggunakan Computer Vision Vardhana, Aryo Romadhon; Gustina, Dian
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 9 No. 1 (2025): IKRAITH-INFORMATIKA Vol 9 No 1 Maret 2025
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v9i1.4374

Abstract

This study discusses the design and development of a web-based application for malariadisease detection using Computer Vision. The main objective of this research is to developa system that can assist medical personnel in detecting malaria infections more quickly andaccurately by utilizing computer vision technology. The proposed system employs theConvolutional Neural Network (CNN) algorithm to analyze microscopic erythrocyteimages obtained from blood samples. Malaria image data used in this study were collectedfrom various online sources as well as through direct observation in hospitals.The systemdevelopment process begins with the collection of malaria image data, which is thenprocessed through preprocessing stages to enhance data quality and prepare it for modeltraining. Once the data is ready, the CNN model is trained using augmented training datato improve the model's generalization. Model evaluation is conducted using test data tomeasure the accuracy and performance of the model in detecting malaria.Evaluation results indicate that the developed CNN model has high accuracy in detecting malaria infections,with satisfactory precision, recall, and F1-score values. The system is also capable ofgenerating detection reports and visualizations that facilitate medical personnel indiagnosis. This system is expected to support efforts to improve malaria diagnosis inhealthcare facilities, particularly in remote areas with limited access to trained medicalpersonnel. Additionally, the system is anticipated to reduce the workload of medicalpersonnel and increase efficiency in the malaria diagnosis process.
Co-Authors Dian Gustina, Dian