Malaria Detection Tool
Upload a blood smear image or download our sample images to test the system
Click to upload or drag and drop
PNG, JPG or JPEG (max 5MB)
Important Note
This tool is designed to assist in the early detection of malaria, but it should not replace professional medical diagnosis. Always consult healthcare professionals for definitive diagnosis and treatment.
About Siaga Malaria Nusantara
Malaria remains a serious health issue in Indonesia, especially in remote and endemic areas. Indonesia is one of the malaria-endemic countries in Southeast Asia, contributing approximately 15.6% of regional cases.
Conventional malaria diagnosis relies on laboratory microscopic examination by experts, a procedure that requires special equipment and is time-consuming. This creates a service gap as hospitals and clinics in remote areas often lack microscopic laboratory facilities, making it difficult to screen patients at risk early.
The Siaga Malaria Nusantara project aims to provide a quick and accurate diagnostic aid tool to support medical personnel without replacing them. This system is expected to detect patients earlier, minimize complications, and accelerate treatment/clinical decisions.
Development Team
Meet the talented team behind Siaga Malaria Nusantara, dedicated to improving malaria detection in Indonesia.
Naila Suqya
Project Lead
Responsible for project management, and creating web mockups using Figma.
Brian Aji Pamungkas
Machine Learning Engineer
Designs, trains, and optimizes the CNN model for accurate malaria detection on blood-smear images.
Adrian Ramadhan
Software Engineer
Implements server-side logic, and integrates the ML model into the web application.
Fitri Mauizah
Data Scientist / Researcher
Conducts data preprocessing, exploratory analysis, and validation of model performance metrics.