Skripsi

PENERAPAN REGRESI RIDGE UNTUK MENENTUKAN FAKTOR-FAKTOR YANG MEMPENGARUHI PERSENTASE PENDUDUK MISKIN DI INDONESIA

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Penilaian

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Ridge Regression is a method to deal with multicollinearity problems in regression modeling problems. This study aims to determine the factors that affect the percentage of poor population in Indonesia based on the Ridge Regression model of the percentage of poor population and determine the factors that affect the percentage of poor population in Indonesia based on the best Ridge Regression model of the percentage of poor population using Stepwise method. The method used is Ridge Regression analysis. The data used is secondary data obtained from the Badan Pusat Statistik Indonesia. The research variables include data on the percentage of the poor population, poverty depth index, poverty severity index, average length of schooling, human development index, regional gross domestic product, and open unemployment rate. The results of multiple regression modeling using the OLS method obtained that there was multicollinearity between independent variables indicated by the value of VIF ≥ 10. Therefore, the multiple regression assumption model is fixed by forming a model with Ridge regression. The results for the Ridge Regression model of the percentage of poor population are factors that affect the percentage of poor population in Indonesia are the poverty depth index, human development index, regional gross domestic product, and open unemployment rate. The results for the best model of the percentage of poor population Ridge Regression using the Stepwise method, namely the factors that affect the percentage of poor population in Indonesia are poverty depth index, poverty severity index, and human development index.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407003828	T146113	T1461132024	Central Library (References)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1461132024

Publisher

Indralaya : Prodi Ilmu Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam., 2024

Collation

xiv, 103 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

510.07

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

-

Subject(s)

kemiskinan
Prodi Ilmu Matematika

Specific Detail Info

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Statement of Responsibility

KA

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