K-Means Algorithm for Mapping by Utilizing Google Maps Imagery
Y A Gerhana*, A P Fuzilesmana, U Syarifuddin, A R Atmadja, M A Ramdhani

Department of Informatics, UIN Sunan Gunung Djati Bandung
*yanagerhana[at]uinsgd.ac.id

Abstract

In several cases, data mapping that is available today has not much done digitally yet. Too much data that is involved in data filling process causing a long mapping process. The purpose of this research is to design the system by implementing K-Means Clustering Algorithm for data mapping using Google Maps imagery. The object of system design in this research is the plantation area in Sukabumi Regency, Indonesia. The system design methodology that used is the UML (Unified Modeling Language) approach. Based on the results of system testing, K-Means Clustering algorithm can determine and cluster the plantation area with potency of commodity with three level, among others high level, medium level, and low level, which is further indicated by spatial data.

Keywords: Cluster, Commodity, Google Maps, K-Means Clustering

Topic: Computer Science