The Effect of Human Development Index on Poverty Model in Indonesia using Penalized Basis Spline Nonparametric Regression.

Authors : Nurul Hasanah; Nurul Fitriyani; Samsul Bahri
article cite 4 Year 2021
source: IOP Conference Series Materials Science and Engineering
Abstract

Abstract Poverty is an issue of special concern to various countries in the world, including Indonesia. One factor that can affect poverty is the Human Development Index (HDI). The aim of this study is to model of the problem of poverty based on HDI. Using nonparametric spline regression was used with the penalized basis spline (PB-Spline) approach, which can overcome the problem of selecting many knot points and the location of knots in spline regression. This study was obtained three models, i.e. model with one knot point, model with two knot points, and model with three knot points. Based on indicators of the value of Generalized Cross Validation (GCV) and the value of Mean Square Error (MSE), the best model was a model with three knots, with smoothing parameter value of 1000, 11.26236 value of GCV and 11.08420 value of MSE.


Concepts :
Advanced Statistical Methods and Models
Statistical Methods and Applications
Data Mining and Machine Learning Applications
article cite 4 Year 2021 source IOP Conference Series Materials Science and Engineering
SDGs
No poverty
Citations by Year
YearCount
2021 4