A STATISTICAL ANALYTICS OF MIGRATION USING BINARY BAYESIAN LOGISTIC REGRESSION
Abstract
Binary logistic regression is utilized in research to understand the relationship between multiple independent variables and a binary response variable. In logistic regression modelling, parameter estimation is regarded as a vital stage. The performance of this estimation is often affected by the sample size and data characteristics, and to deal with this problem, the Bayesian method can be employed as an estimation. This research aims to use Regression Logistic with Bayesian estimation to figure out the determinant of recent in-migrants status in Special Region of Yogyakarta 2021, where Yogyakarta’s recent in-migrants in 2021 took the first position in Indonesia, whereas this city has the lowest regional minimum wage in Indonesia. The Bayesian method was used in this study to obtain a better estimate than previous studies using maximum likelihood estimation, because Bayesian is unbiased for unbalanced cases which are often found in logistic regression. This research results show that particular variables such as resident age, resident marital status, resident main activities, resident latest education, and resident homeownership have significant effect on resident migrating to Special Region of Yogyakarta, Indonesia
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