Early Detection of Disease Outbreaks: A Monitoring System for Sleman Regency

Abstract

In early 2025, Indonesia faced a surge in infectious diseases, with 6,000 Dengue Fever and 28 deaths by January, and 889,000 tuberculosis cases by March. An outbreak or “Kejadian Luar Biasa” (KLB) is marked by a significant rise in illness or death within a period. However, according to the Sleman Regency Health Office, the existing Early Warning and Response System remains suboptimal in detecting such events. To improve early detection, a Disease Outbreak Monitoring System was developed using the Waterfall Method. This system features an interactive dashboard, data storage for patients and health centers, automatic KLB detection, and a feedback mechanism. Testing has demonstrated that the system improves accuracy and responsiveness, providing a promising solution for early outbreak detection and prevention.