Implementation of Hotspot Analysis Using the Kernel Density Estimation (KDE) Algorithm for WebGIS-Based Visualization of Culinary MSME Businesses: A Case Study of Makassar City - Mega Puspita Trianjani; Syamsu Alam; muhammad ashdaq (Universitas Negeri Surabaya, 2026)
This study addresses the challenge of mapping the potential of culinary MSMEs (Micro, Small, and Medium Enterprises) in Makassar City by developing an interactive WebGIS-based visualization system. Using a Research and Development (R&D) approach, location data obtained from OpenStreetMap (OSM) were analyzed using the Kernel Density Estimation (KDE) algorithm to identify business hotspots. The findings reveal clear spatial concentration patterns, with the highest hotspot intensities located in the districts of Panakkukang, Rappocini, and Tamalate. A key contribution of this research is the identification of a substantial digital gap, as approximately 94% of officially registered MSMEs are not represented on digital map platforms. In response, the developed WebGIS system fulfills a dual role: it functions as an analytical tool for assessing business potential and as a strategic diagnostic instrument to support more targeted MSME digitalization initiatives.