@phdthesis{digilib51929,
           month = {April},
           title = {MODEL REGRESI NONPARAMETRIK B-SPLINE (STUDI KASUS: PERSENTASE KEMISKINAN DAN FAKTOR-FAKTOR YANG MEMPENGARUHI PERSENTASE PENDUDUK MISKIN PROVINSI JAWA BARAT TAHUN 2017)},
          school = {UIN SUNAN KALIJAGA YOGYAKARTA},
          author = {NIM.: 15610026 Risma Nur Sukmawati},
            year = {2019},
            note = {Pembimbing: M. Farhan Qudratullah, M.Si.},
        keywords = {Regresi Nonparametrik, Persentase Kemiskinan, Regresi B-Spline,
Titik Knot.},
             url = {https://digilib.uin-suka.ac.id/id/eprint/51929/},
        abstract = {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 :
Y? ? ? ? ? ? ?
? ? ? ? ? ?
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.}
}