Multivariate adaptive regression splines and bootstrap aggregating multivariate adaptive regression splines of poverty in Central Java

Kharisma, Ria Dhea LN, Juhari, Juhari and Rosa, Ramadani A . (2021) Multivariate adaptive regression splines and bootstrap aggregating multivariate adaptive regression splines of poverty in Central Java. Cauchy: Jurnal Matematika Murni dan Aplikasi, 6 (4). pp. 238-245. ISSN 2477-3344

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Abstract

Poverty population is one of the serious problems in Indonesia. The percentage of population poverty used as a means for a statistical instrument to be guidelines to create standard policies and evaluations to reduce poverty. The aims of the research are to determine model population poverty using Multivariate Adaptive Regression Spline and Bagging MARS then to understand the most influence variable population poverty of Central Java Province in 2018. The result of this research is the Bagging MARS model showed better accuracy than the MARS model. Since, GCV in the Bagging MARS model is 0,009798721 and GCV in the MARS model is 6,985571. The most influence variable population poverty of Central Java Province in 2018 based on MARS model is the percentage of the old school expectation rate. Then, the most influentce variable based on Bagging MARS model is the number of diarrhea disease

Item Type:	Journal Article
Keywords:	multivariate adaptive regression splines; bootstrap aggregating; generalized crossvalidation; poverty
Subjects:	01 MATHEMATICAL SCIENCES > 0104 Statistics > 010405 Statistical Theory 01 MATHEMATICAL SCIENCES > 0104 Statistics
Divisions:	Faculty of Mathematics and Sciences > Department of Mathematics
Depositing User:	Juhari Juhari
Date Deposited:	31 May 2021 10:56

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