REGRESI NONPARAMETRIK SPLINE MULTIVARIAT UNTUK MENENTUKAN FAKTOR YANG MEMPENGARUHI KEMISKINAN DI SULAWESI SELATAN

Muh. Qodri Alfairus; Muhammad Arif Tiro; Muhammad Kasim Aidid

doi:10.35580/variansiunm23857

REGRESI NONPARAMETRIK SPLINE MULTIVARIAT UNTUK MENENTUKAN FAKTOR YANG MEMPENGARUHI KEMISKINAN DI SULAWESI SELATAN

Muh. Qodri Alfairus^(1*), Muhammad Arif Tiro⁽²⁾, Muhammad Kasim Aidid⁽³⁾,

(1) Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Makassar, Indonesia
(2) Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Makassar, Indonesia
(3) Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Makassar, Indonesia
(*) Corresponding Author

DOI: https://doi.org/10.35580/variansiunm23857

Abstract

Poverty is a condition of economic inability to meet the average standard of living of the people in an area. The percentage of poverty in Indonesia reaches 9.41% or reaches 25.14 million people. On the island of Sulawesi, the poverty percentage of the population is still quite high. One of the regions with the highest percentage of poverty in Sulawesi Island is South Sulawesi Province with a poverty percentage of 8.69%, which is ranked 18th nationally. Poverty can be seen with two indicators, namely the percentage of poor people and the poverty depth index. This study uses 5 factors that are thought to affect poverty in South Sulawesi which include the Literacy Rate, Average Length of Schooling, Open Unemployment Rate, PDRB Per Capita, and School Participation Rate. The data used in this research is data from 2018 which comes from the Central Statistics Agency of South Sulawesi. The method used to model the percentage of poor population and the depth of poverty index is a multivariate spline nonparametric regression. This method is used because it is suitable in modeling data whose patterns change at certain subintervals. The best model that is produced from the nonparametric multi-variate spline regression in South Sulawesi is the knot 2 model and the most influencing factors are the School Participation Rate and GRDP Per Capita. This method is used because it is suitable in modeling data whose patterns change at certain subintervals. The best model that is produced from the nonparametric multi-variate spline regression in South Sulawesi is the knot 2 model and the most influencing factors are the School Participation Rate and GRDP Per Capita. This method is used because it is suitable in modeling data whose patterns change at certain subintervals. The best model that is produced from the nonparametric multi-variate spline regression in South Sulawesi is the knot 2 model and the most influencing factors are the School Participation Rate and GRDP Per Capita

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