Multicollinearity problem-solving with Jackknife Ridge Regression: A case study on slum conditions in Bone Bolango

Dwi Putri Juniar Adam; Salmun K. Nasib; Amanda Adityaningrum

doi:10.12928/bamme.v5i1.12759

Authors

Dwi Putri Juniar Adam Universitas Negeri Gorontalo
Salmun K. Nasib Universitas Negeri Gorontalo
Amanda Adityaningrum Universitas Negeri Gorontalo https://orcid.org/0000-0002-9874-7641

DOI:

https://doi.org/10.12928/bamme.v5i1.12759

Keywords:

Jackknife Ridge Regression, Multicollinearity, Slum conditions

Abstract

Slum conditions in Indonesia, particularly in Gorontalo Province's Bone Bolango District, are a significant challenge to sustainable development. This research aims to identify the key factors contributing to slum conditions in the strategic economic areas of Kabila, Suwawa, and Tilongkabila using Jackknife Ridge Regression (JRR) analysis to address multicollinearity and overfitting issues. Data from the Regional Development Planning Board (BAPPEDA) Bone Bolango District's 2023 document was used, with a sample of 40 urban villages and villages. The result showed that there is a high collinearity between two independent variables, necessitating the use of JRR. The JRR model identified seven independent variables significantly related to slum value. The regression model explained 83% of the variability in slum conditions. This study provides methodological depth through the JRR framework, which enables accurate slum analysis where traditional models (like OLS) tend to fall short. It emphasizes the need for Bone Bolango to prioritize its policy initiatives by focusing on the seven independent variables. Additionally, the framework demonstrates scalability, making it adaptable to other Indonesian provinces that face similar challenges with slum data.

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Multicollinearity problem-solving with Jackknife Ridge Regression: A case study on slum conditions in Bone Bolango

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