Eksplorasi Small Area Estimation (SAE) Data SUSENAS Triwulanan dengan Add-Ins Rexcel

Abstract

Nowadays, the demand of small area data of BPS-Statistics Indonesia is increasing. This condition needs further study about SAE for BPS data. By using SUSENAS quarterly, we want to see how SAE can produce better accuracy for estimation value in small area than design-based. The result show that SAE EBLUP-Fay Herriot can produce better estimation with lower MSE than design-based estimation. This research also create tools to calculate this estimation. The tools was wrapped in Add-Ins Rexcel based on  Graphical User Interface ( GUI ).

Keywords: EBLUP Fay Herriot,  SAE, design-based, SUSENAS, Add-Ins, Rexcel