Characteristics and segmentation of social problems with kohonen self-organizing maps

Abstract

Indonesia is a country with a low Human Development Index, it shows the number of quality and healthy standard in Indonesia is still poor. Indonesia also have various social problems such as overcrowding, poverty, unemployment, bad education level .This problem can bring negative impact for our society like increasing of crime rate. For identification phase of social problems and crime, Indonesian government does not integrate social problems which is identified can affect the crime and use descriptive statistics only. Further diagnosis required for cases of social issues. The purpose and benefits of this research is to determine the characteristics of the social problems in Indonesia, introduce and make segmentation using Kohonen Self Organizing Maps algorithm. Hopefully the results of this analysis can helps government for make public policy in general, specifically future policy about social problems in Indonesia. Using Kohonen algorithm effective for visualizing of high-dimensional data by reducing the dimensions of ann-dimensional input into lower dimension while maintaining its original topological relations. Based of clustering result of provinces in Indonesia, it divided into 5 group and each group has similar characteristics.