Latent Class Cluster for Clustering Villages Based on Socio-economic Indicators in 2018

Abstract

Latent class analysis (LCA) is a statistical method used to classify units into unobserved (latent) variable classes, so-called clusters. In this article, we introduce LCA to demonstrate its use for village groupings. We applied LCA on data processed from the census conducted by BPS-Statistics Indonesia, namely the village potential (Podes) data 2018. The Podes data is used to extract the socio-economic characteristics of a village. The empirical results of the LCA application show that the villages in the Banyumas Regency are grouped into three classes/clusters.