Application of the Self Organizing Maps (SOM) Method in Clustering Based on Indicators of Need for Social Welfare Services (PPKS) West Java province

Abstract

The province of West Java in Indonesia has witnessed a rise in its impoverished population. Being the most populous province in Indonesia, West Java faces complex social welfare issues due to its large population. This study aims to conduct cluster analysis to identify district/city clusters in West Java province and determine the characteristics of these groups based on the indicators of the Need for Social Welfare Services (PPKS). The self-organizing maps (SOM) method will be utilized for this analysis. SOM is an unsupervised learning method, in which the training process does not require supervision (target output) which produces input representations in two dimensions (maps). In this study, the results obtained were 3 clusters where cluster 1 which consisted of 24 districts/cities had a relatively high average score for each member in the cluster, then cluster 2 which consisted of Cianjur and Karawang districts showed high social welfare problems compared to other clusters, and for cluster 3 which consists of Bandung regency, it shows that the most prominent social welfare problem is the indicator of socio-economic vulnerability of women, with an average of 34,549 cases/year. Based on the results obtained, it is necessary to make the right decisions regarding allocations, resources, more effective service planning, and the development of more targeted social welfare programs.