Implementation of Spatial Analysis Using KNN-5 in GIS for Mapping Mushroom Houses in Karawang Regency

Abstract

This research aims to develop a Geographic Information System (GIS) to map the locations of straw mushroom farms in Karawang Regency by applying spatial analysis based on the K-Nearest Neighbors algorithm with k = 5. This approach examines the spatial proximity relationship between mushroom production sites and the nearest markets to inform location-based distribution decisions. The research method employs a quantitative approach through mapping, geographic coding, and analysis of geographic distances, which are integrated into the GIS. Spatial data are obtained from field observations and collected from mushroom farmers, then analyzed using distance calculations based on geographic coordinates. The results show that the K-Nearest Neighbors analysis with k = 5 can dynamically identify the nearest markets and more objectively represent the spatial relationship between production and markets than a static radius approach. Additionally, proximity analysis between farms reveals local-scale spatial clustering patterns, while radius analysis provides an initial overview of limited spatial accessibility. Integrating the analysis results into the Geographic Information System enables comprehensive spatial visualization and supports more efficient, data-driven decision-making for straw mushroom distribution.