Data Mining of The Grouping And Mapping of The Health Centers in Sleman Regency With K-Means Clustering Algorithm

Abstract

This research which is a grouping and mapping system of Puskesmas (public health center) is one solution to obtain information related to areas that have adequate Puskesmas services. With the help of a geographic information system, it is able to describe the state of the Sleman district based on the availability of health centers per sub-district. In a geographic information system, the information produced is in the form of visual images that make it easier for the public to read the information provided. This study uses data from health workers who work in health centers and were grouped first using the k-means method. The reason for grouping them first was to make it easier to map the existing health centers, while the K-means method was chosen because it has a high accuracy to the size of the object, so this algorithm is relatively more scalable and efficient for processing large numbers of objects. In addition, the K-Means algorithm is not affected by the order of objects.