Spatial Mapping of Endemic Diseases in Lamongan Regency Using Natural Breaks Clustering - Much Chafid; Ahmad Walid Hujairi; Muhammad Turmudzi; Arna Fariza; Mohammad Robihul Mufid; Shintia Dewi Rahmawati (Jurusan Teknologi Informasi Politeknik Negeri Jember, 2025)
Endemic diseases are health problems that require continuous monitoring to prevent their spread. However, the lack of interactive spatial data visualization can make it difficult for health agencies to analyze the distribution of diseases effectively. This study aims to build a spatial mapping system for endemic diseases in Lamongan Regency using the Natural Breaks clustering method. The data used in this study include sub-district data, population, and endemic diseases obtained from the Lamongan Regency health profile website. The system was developed using the Laravel 10 framework and MySQL database, with Metabase as a data visualization tool. The geovisualization method is applied to display the distribution of diseases in the form of interactive maps based on sub-districts. The system allows users to trace the spatial and temporal trends of endemic diseases more easily. The test results show that the system is able to display information accurately and interactively, so that it can help health agencies in monitoring and planning regional health policies more effectively