Socio Spatial Analysis of Manpower in East Java 2022

ABSTRACT: There are 25 regencies and cities in East Java that are included in the priority areas foraccelerating the elimination of extreme poverty. In some areas, unemployment is a complex problem and noteasy to solve, so solving it is one of the priorities of macroeconomic policy. In 2022, of the 22,869 millionpeople in the labor force in East Java, 1,255,719 of them are unemployed. This condition is exacerbated by thenumber of unemployed people who are dominated by high school graduates. Unemployment Rate in each regionof East Java is very diverse, although Unemployment Rate East Java has decreased significantly, not allregencies and cities have also decreased. This condition is in line with Lewandowska-Gwarda’s opinion, whichreveals that the problem of unemployment is a heterent economic problem because it is influenced bygeographical spatial effects. This study aims to identify spatial patterns and identify and analyze factors thataffect unemployment in each region in East Java. Identify spatial patterns of unemployment in East Java usingthe spatial autocorrelation method, while to identify and analyze factors affecting Unemployment Rate in EastJava using GWR. For GWR, variable X is used which consists of economic growth and Regional MinimumWages. The results show a moran index value of 0.368 which means ≠0 with a kurtosis of 2.876 so that it showsa positive spatial autocorrelation with indications of clustered patterns. While the results of the GWR analysisobtained that Unemployment Rate in each district and city area in East Java was influenced by MSE variables,while economic growth variables did not have a significant effect.

KEYWORDS –Unemployment Rate, Spatial Autocorrelation, Moran Index, GWR