%0 Thesis
%9 Skripsi
%A Risma Nur Sukmawati, NIM.: 15610026
%B FAKULTAS SAINS DAN TEKNOLOGI
%D 2019
%F digilib:51929
%I UIN SUNAN KALIJAGA YOGYAKARTA
%K Regresi Nonparametrik, Persentase Kemiskinan, Regresi B-Spline,  Titik Knot.
%P 192
%T MODEL REGRESI NONPARAMETRIK B-SPLINE (STUDI KASUS: PERSENTASE KEMISKINAN DAN FAKTOR-FAKTOR YANG MEMPENGARUHI PERSENTASE PENDUDUK MISKIN PROVINSI JAWA BARAT TAHUN 2017)
%U https://digilib.uin-suka.ac.id/id/eprint/51929/
%X Regression analysis became the basis for conclusion (inferencing) about  the functional relationship between predictor variables and response variable. In  regression analysis there are two approaches, called parametric approach and  nonparametric approach. A nonparametric approach is not banded by normality  assumption and the data given as independence of search the curve regression so  this approach are very flexibility and objective. Nonparametric regression  approaches that are often used include spline regression, which is one type of  polynomial piecewise, a polynomial that has a nature segmented. Spline approach  has a basic function that commonly used, which is B-Spline.  Data in this research is poverty percentage regencies / cities of West Java  Province in 2017. As dependent variable is the percentage of the poor people as  Y and independent variables are the open unemployment rate as 1 X and the  average length of school as 2 X .  The best B-Spline regression model for estimating the percentage data of  the poor people in West Java using the Weighted Least Square method is :  Yˆ               1,2 1 0,2 1 1,2 1  1,2 2 0,2 2 1,2 2  0,9825 ( ) 3,3417 ( ) 0,9575 ( )  11,9249 ( ) 10,1563 ( ) 4,0192 ( )  N x N x N x  N x N x N x    with the MSE value is 3,9776 then determination value is 58.05% and the GCV  value is 5.9866.
%Z Pembimbing: M. Farhan Qudratullah, M.Si.