Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Eksakta : Berkala Ilmiah Bidang MIPA
Mardha Tillah
Mathematics Department, FMIPA, Universitas Andalas, Indonesia
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Modeling of Human Development Index Using Ridge Regression Method Ferra Yanuar; Mardha Tillah; Dodi Devianto
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 19 No. 2 (2018): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1245.808 KB) | DOI: 10.24036/eksakta/vol19-iss2/134

Abstract

This article aims to model factors affecting HDI (Human Development Index) in North Sumatera by 2015 using ridge regression method. This ridge regression method is used because in the IPM data there is a multicolinearity problem so that the least squares regression method, as regression method commonly used in statistical modeling, is not suitable for use any more. This study compares the models resulting from the use of the least squares method and the ridge regression method to the HDI data. This study proves that the ridge regression method produces a better model and can eliminate the multicolinearity effect, while the least squares method can not. The significant factors in affecting HDI on North Sumtera data in 2015 are Average School length and Total expenditure / capita / month. The indicator of the goodness of this ridge regression model is 81.81% which means that the model is good and could be accepted.
Co-Authors Devianto, Dodi Yanuar, Ferra