IMPLEMENTASI GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION PADA LAJU PERTUMBUHAN PENDUDUK DI BOJONEGORO

Population Growth Rate is the rate at which influencing factors increase and decrease population size. The development of large populations in regional governments causes uncontrolled population growth rates. The population growth rate in Bojonegoro Regency from 2019 to 2020 experienced a significan...

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Bibliographic Details
Main Authors: Nur Mahmudah, Nuraini Khoiriyah
Format: Article
Language:English
Published: Universitas Bina Bangsa 2023-12-01
Series:Jurnal Lebesgue
Subjects:
Online Access:https://lebesgue.lppmbinabangsa.id/index.php/home/article/view/485
Description
Summary:Population Growth Rate is the rate at which influencing factors increase and decrease population size. The development of large populations in regional governments causes uncontrolled population growth rates. The population growth rate in Bojonegoro Regency from 2019 to 2020 experienced a significant increase of 0.96%. The increase in population has an impact on the emergence of various problems in the economic and social fields. This problem requires effective and comprehensive spatial modeling, namely Geographically Weighted Logistic Regression (GWLR) with Fixed Gaussian and Adaptive Gaussian weighting. GWLR modeling aims to determine the implementation of knowledge and insight into the factors that influence the rate of population growth in each area of ​​Bojonegoro District. based on the results of GWLR modeling with the Akaike Index Criteria (AIC) on the Fixed Gaussian kernel function of 33.91. This value identifies that the population growth rate modeling in each sub-district has different values. This difference can be seen from 6 sub-districts which are significantly influenced by the number of births and 5 sub-districts are significantly influenced by the number of couples of childbearing age who participate in family planning. The results of modeling predictions (GWLR) in Bojonegoro Regency show that 11 sub-districts have low growth rate categories while 17 sub-districts have high population growth rate values
ISSN:2721-8929
2721-8937