Affiliations: [a] Department of Mathematics, Faculty of Mathematics and Natural Science, Andalas University, Kampus Limau Manis, Padang, Indonesia | [b] Department of Political Sciences, Faculty of Social and Political Sciences, Andalas University, Kampus Limau Manis, Padang, Indonesia
Correspondence:
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Corresponding author: Ferra Yanuar, Department of Mathematics, Faculty of Mathematics and Natural Science, Andalas University, Kampus Limau Manis, Padang, Indonesia. E-mail: [email protected].
Abstract: Data on the number of health insurance participants at the subdistrict level is crucial since it is strongly correlated with the availability of health service centers in the areas. This study’s primary purpose is to predict the proportion of health and social security participants of a state-owned company named Badan Penyelenggara Jaminan Sosial Kesehatan (BPJS) in eleven subdistricts in Padang, Indonesia. The direct, ordinary least square, and hierarchical Bayesian for small area estimation (HB-SAE) methods were employed in obtaining the best estimator for the BPJS participants in these small areas. This study found that the HB-SAE method resulted in better estimation than two other methods since it has the smallest standard deviation value. The auxiliary variable age (percentage of individuals more than 50 years old) and the percentage of health complaints have a significant effect on the proportion of the number of BPJS participants based on the HB-SAE method.
Keywords: Hierarchical bayesian (hb), small area estimation (SAE), health and social security participants
