TY - JOUR
T1 - Modeling of Human Development Index in Papua Province Using Spline Smoothing Estimator in Nonparametric Regression
AU - Rahmawati, D. P.
AU - Budiantara, I. N.
AU - Prastyo, D. D.
AU - Octavanny, M. A.D.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2021/2/15
Y1 - 2021/2/15
N2 - The development goal of a country must be focused on the quality of human life to achieve prosperity. One important indicator for measuring the success of a country's development is the Human Development Index (HDI). In 2018, Papua was the province with the lowest HDI in Indonesia. Special attention is needed to improve HDI in Papua Province, one of them is by paying attention to the variables that affect HDI such as population growth rate, percentage of poor population, and economic growth. The relationships between HDI and the predictor variables do not have a clear pattern and tend to change at certain subintervals. This case can be approached using Spline Smoothing in multivariable nonparametric regression. Spline Smoothing is a type of estimator in nonparametric regression that has an excellent ability to handle data that tend to change at certain subintervals. Therefore, the purposes of this study are to obtain the form of Spline Smoothing estimator function in multivariable nonparametric regression, estimate the function and apply it to the HDI in Papua Province. The empirical results of modeling HDI in Papua Province show that it can be adequately applied which gives GCV = 58.108, R2 = 99.77% and RMSE = 0.0505.
AB - The development goal of a country must be focused on the quality of human life to achieve prosperity. One important indicator for measuring the success of a country's development is the Human Development Index (HDI). In 2018, Papua was the province with the lowest HDI in Indonesia. Special attention is needed to improve HDI in Papua Province, one of them is by paying attention to the variables that affect HDI such as population growth rate, percentage of poor population, and economic growth. The relationships between HDI and the predictor variables do not have a clear pattern and tend to change at certain subintervals. This case can be approached using Spline Smoothing in multivariable nonparametric regression. Spline Smoothing is a type of estimator in nonparametric regression that has an excellent ability to handle data that tend to change at certain subintervals. Therefore, the purposes of this study are to obtain the form of Spline Smoothing estimator function in multivariable nonparametric regression, estimate the function and apply it to the HDI in Papua Province. The empirical results of modeling HDI in Papua Province show that it can be adequately applied which gives GCV = 58.108, R2 = 99.77% and RMSE = 0.0505.
KW - Human Development Index
KW - Multivariable Nonparametric Regression
KW - Penalized Least Square
KW - Spline Smoothing
UR - http://www.scopus.com/inward/record.url?scp=85101767164&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1752/1/012018
DO - 10.1088/1742-6596/1752/1/012018
M3 - Conference article
AN - SCOPUS:85101767164
SN - 1742-6588
VL - 1752
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012018
T2 - 3rd International Conference on Statistics, Mathematics, Teaching, and Research 2019, ICSMTR 2019
Y2 - 9 October 2019 through 10 October 2019
ER -