ANALYSIS OF POVERTY DATA IN BENGKULU CITY BY SMALL AREA ESTIMATION USING PENALIZED SPLINES REGRESSION

This study aims to analyze poverty data in Bengkulu City. The method of this study is Small Area Estimation
(SAE) with penalized splines regression approach. Then descriptive statistical analysis is carried out. The data
used is the Bureau of Statistics (BPS) Of Bengkulu with some poverty indicators as predictor variables. The
results showed the best spline model is a model that is considered linear spline with some node points.
Evaluation of model used optimal GCV. The results of descriptive statistical analysis of the average of per
capita outcome at the village level in the city of Bengkulu using the extensive estimation method with the pspline
regression approach has an average value of Rp.1,009,817.20. About 75% of urban villages in the city
of Bengkulu have an average per capita yield of Rp 1,244,188.15 and the twenty-five percent of urban villages
in Kota Bengkulu have an average per capita outcome about Rp 753.527.25. The high average per capita
outcome is in the Kebun Dahri Village Rp. 3.115.614,20 and the lowest outcome from the Padang Nangka
Village that is Rp 439.830.40.