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Submitted
Dec 24, 2023
Accepted
Dec 30, 2023
Published
Dec 31, 2023
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Abstract

Poverty is a situation where a person experiences difficulty in meeting basic needs. There are several factors that influence poverty, including population, unemployment, gross regional domestic product, human development index, average years of schooling and labor force participation rate. Therefore, it is necessary to carry out regression analysis to determine the relationship between one variable and other variables. One method for estimating regression parameters is the least squares method. Some classic assumptions are not met because there are outlier data. Outliers are data that do not follow the overall distribution pattern, so a method is used that can overcome outliers, namely the S-estimation robust regression method with the Tukey bisquare weighting function. The results of the research show that the best model was obtained from robust S-estimation regression with Tukey bisquare weighting, namely factors that influence the level of poverty on the island of Sulawesi, namely Population Number ), Human Development Index ( ), Average Years of Schooling ( ) and, Force Participation Level. Work .

Keywords

Regression Analysis Poverty Outliers Robust Regression

Article Details

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How to Cite
Saputri, S., Nur’eni, & Masyitah Meliyana R, S. (2023). REGRESSION ANALYSIS OF ROBUST ESTIMATION-S WITH TUKEY BISQUARE WEIGHTING ON POVERTY LEVEL ON SULAWESI ISLAND. Parameter: Journal of Statistics, 3(2), 84-92. https://doi.org/10.22487/27765660.2023.v3.i2.16923

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