Interaction Determining Factors From Regency / City Region in East Java

Abstract

This study aims to calculate the strength of interaction between regions and determine the variables determining the level of interaction between regions. This research was conducted in the area of East Java province with the object of 39 regencies and cities using the variable mileage, educational facilities, and health facilities. The data used are secondary data sourced from the Central Statistics Agency of East Java, meanwhile the analytical tool used is gravity analysis and regression analysis, with the regression model used is panel data regression, the Random Effect model. The results showed that the areas in the interaction category were weak, namely the southern part of East Java, the western part and the eastern part while those in the interaction category were in the middle eastern part of Java. Category of regions with strong interaction are Gerbang kertosusila and surrounding areas. From the random effect model regression analysis it is known that the distance, education and health facilities variables together influence 95% of the level of interaction between regions and the most dominant variable is the distance between regions which has a regression coefficient of -62480222. Health facility variable has a significant positive effect while education facility variable has no effect on interactions between regions. Therefore, in order for equitable development to be realized immediately, the distance between regions must be shortened by improving the quality of roads, construction of new roads and toll roads, especially in the southern, eastern and eastern parts of Java.

Gwrpca Algorithmic Framework: Analyzing Spatial Dynamics of Poverty in East Java Province

“…One of Indonesia's most populous provinces, East Java, exhibits complicated dynamics in its attempts to combat poverty. East Java's regencies and cities exhibit notable disparities in income distribution and resource accessibility, notwithstanding the country's swift economic expansion [2]. There are geographical differences in poverty in East Java, and spatial data is essential to comprehending these dynamics [3].…”