Car Ownership Modeling in Aceh Province Using a Spatial Regression Approach

https://doi.org/10.58451/ijebss.v1i03.41

Authors

  • Hikmah Mulyadi Syiah Kuala University
  • Renni Anggraini Universitas Syiah Kuala,Banda Aceh
  • Zurnila Marli Kesuma Universitas Syiah Kuala,Banda Aceh

Keywords:

Modeling, Vehicle ownership, Private cars, Spatial regression, Geoda

Abstract

The rise in car ownership in Aceh Province has been driven by population growth and economic development. The location of the owner's residence impacts vehicle ownership. There are common spatial dependencies in this area, meaning the significance of an observation in one area is influenced by its importance in another. Factors such as population, regional income, wages and salaries, area size, and road length are believed to impact vehicle ownership. This study aimed to determine the variables affecting vehicle ownership in Aceh Province. Spatial regression analysis was used to identify the determinants of vehicle ownership in Aceh Province. Secondary data was obtained from the Aceh Province One-Stop Administration System Office (SAMSAT) for vehicle ownership documentation, the Aceh Province Wealth and Income Service for vehicle ownership recap data, and other sources such as the Central Bureau of Statistics of Aceh Province for information on population, regional income, wages/salaries, area, road length, and ages. The results showed that car ownership is dependent on geography. The Spatial Error Model (SEM) with an Akaike Info Criterion (AIC) value of 107,919 was found to be the best spatial regression model. Population (X1), regional income (X2), road length (X5), and age over 17 (X6) were found to be the parameters with a significant level of 5% that impact vehicle ownership in Aceh Province.

Published

2023-02-23