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Research Article Open access CC BY 4.0

Determination of Recent In-Migrants in Yogyakarta using Bayesian Regression Logistics

Devi Azarina Manzilir Rohmah, Ani Budi Astuti, Achmad Efendi

Asian Journal of Probability and Statistics · pp. 1–14 · Published 25 Apr 2023

10.9734/ajpas/2023/v22i3483

Abstract

Aims: This research aims to find out the status determinant of recent in-migrants entering the province of Yogyakarta, Indonesia in 2021 with Bayesian logistic regression combined with a nonlinear principal component analysis in the process of forming a latent variable. Study Design:  Quantitative Design. Place and Duration of Study: This research was carried out in the city of Yogyakarta with the data used is 1 year data throughout 2021. Methodology: The data were obtained from the results of national socio-economic surveys (SUSENAS) KOR in March 2021. Results: The research results indicate that particular variables such as age, resident latest education, the status of main activities, the status of residential ownership, housing quality, and asset ownership have significant influences on recent in-migrants entering the Province of Yogyakarta, Indonesia. Conclusion: This research concludes that the Bayesian approach in logistic regression with iteration 1,000,000, 4 thinning interval, and 500.000 burn-in indicates that of seven variables, six variables with significant influences on the status of recent migrants entering the Province of Yogyakarta consist of age (X1), latest education (X3), main activities (X4), house ownership (X5), housing quality (X6), and asset ownership (X7). Of these six variables, the younger resident, the resident with high school or equal as their latest education, the resident currently working as their main activity, the resident renting a house, and the resident with high housing quality score and high asset ownership score are more likely to do recent migration to the Province of Yogyakarta.

Recent in-migrants Bayesian logistic regression Yogyakarta

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