Science and Technology Indonesia
Vol. 8 No. 2 (2023): April

Spatial Autoregressive Quantile Regression with Application on Open Unemployment Data

Ferra Yanuar (Department of Mathematics and Data Science, Andalas University, 25163, Indonesia)
Tasya Abrari (Department of Mathematics and Data Science, Andalas University, 25163, Indonesia)
Izzati Rahmi HG (Department of Mathematics and Data Science, Andalas University, 25163, Indonesia)
Aidinil Zetra (Department of Political Sciences, Andalas University, 25163, Indonesia)



Article Info

Publish Date
15 Apr 2023

Abstract

The Open Unemployment Level (OUL) is the percentage of the unemployed to the total labor force. One of the provinces with the highest OUL score in Indonesia is West Java Province. If an object of observation is affected by spatial effects, namely spatial dependence and spatial diversity, then the regression model used is the Spatial Autoregressive (SAR) model. Quantile regression minimizes absolute weighted residuals that are not symmetrical. It is perfect for use on data distribution that is not normally distributed, dense at the ends of the data distribution, or there are outliers. The Spatial Autoregressive Quantile Regression (SARQR) is a model that combines spatial autoregressive models with quantile regression. This research used the data regarding OUR in West Java in 2020 from the Central Bureau of Statistics. This study develops to modeling the Open Unemployment Level in all province in Indonesia using modified spatial autoregressive model with the quantile regression approach. This study compares the estimation results based on SAR and SARQR models to obtain an acceptable model. In this study, it was found that the SARQR model is better than SAR at dealing with the problems of dependency and diversity in spatial data modeling and is not easily affected by the presence of outlier data.

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Journal Info

Abbrev

JSTI

Publisher

Subject

Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Materials Science & Nanotechnology Physics

Description

An international Peer-review journal in the field of science and technology published by The Indonesian Science and Technology Society. Science and Technology Indonesia is a member of Crossref with DOI prefix number: 10.26554/sti. Science and Technology Indonesia publishes quarterly (January, April, ...