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The data collection process for recipients of disability social assistance at Dinas Sosial has been going well, but the existing dataset is still in the form of raw data that has not been analyzed for the importance of the Dinas Sosial or Cirebon Satu data. The purpose of this study is to design a Geospatial Information System that can help to analyze, classify, and visualize spatial data from recipients of disability social assistance based on age. The methods used are fuzzy and k-means methods. Fuzzy is a method that can be used to group the age of recipients of disability social assistance and find out the degree of membership. The use of the k-means method is one method that is suitable for use in age clustering. Age will be grouped into three clusters, namely cluster 1 (Young), cluster 2 (Middle-Aged) and cluster 3 (Old). The results of this research are in the form of dataset analysis using the fuzzy k-means method in Microsoft Excel, map analysis in QGIS and maps in html format. After testing, the clustering results of fuzzy and k-means methods carried out in two iterations are "SAME". The results of map visualization are also good. The conclusion of this study is that the Geospatial Information System runs well and can be used to assist Dinas Sosial and for the importance of Cirebon Satu Data
Wijaya et al. (Fri,) studied this question.