DOI: https://doi.org/10.14710/j.gauss.15.1.%25p

REGRESI ROBUST ESTIMASI-M UNTUK PEMODELAN TINGKAT PENGANGGURAN TERBUKA (TPT) DI PROVINSI JAWA TENGAH

*octa choerunnisa  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Mustafid Mustafid  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Sudarno Sudarno  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2026 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

Regression analysis can be used to overcome the outlier problem with robust regression. The M-estimation robust regression method is an estimation approach that is the simplest computationally and theoretically. The purpose of using the robust regression method is because there is an outlier problem in the data. This research will create a model on open unemployment rate data in Central Java in 2022 which involves variables including average length of schooling, population, number of poor people, minimum wage, and per capita expenditure. Based on the Ordinary Least Squares (OLS) regression equation, it shows that there is a violations of assumptions and outlier data is detected. So it is necessary to carry out robust regression to overcome the outlier problem. In the test carried out using M-estimation robust regression, the best robust regression model was obtained  = -5,899 + 0,0192 X3+ 0,0000024 X4+0,00036 X5. The M-estimation robust regression model can be concluded that total variation in the open unemployment rate in Central Java in 2022 is explained by the number of poor people, minimum wages, and per capita expenditure by 31.39%, and the MSE value is 2.143382.

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Keywords: Robust Regression; Outliers; M-Estimation; Open Unemployment Rate

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