Analisis Regresi Data Panel Untuk Pemodelan Kemiskinan Pulau Sumatera Dengan Variabel Pendidikan Tahun 2016 – 2021

Abstract

The poverty rate on the island of Sumatra is still categorized as high.
This is due to the lack of professional human resources who can
produce and develop their own natural resources. One of the
Government's current priority programs is human resource
development. Human resource development can be implemented by
taking into account the level of education of the community. In other
words, taking into account the level of education will be able to reduce
poverty. Therefore, in this study, poverty modeling in 10 provinces on
the island of Sumatra will be carried out and analyze what factors
influence poverty. The research method used is panel data regression,
where the data involves cross section and time series. In this study, the
data obtained are secondary data sourced from the Central Statistics
Agency (BPS). There are three dependent variables used, namely the
percentage of poor people, the poverty depth index and the poverty
severity index. While the independent variables used are education
variables which include Literacy Rate, Average Years of Schooling,
Gross Enrollment Rate (APS), Pure Participation Rate (APM) and
School Participation Rate (APS). The results showed that the best
estimation method for the three dependent variables was the Random
Effect Model estimation method. The independent variables that are
equally significant for the three models include literacy rates and pure
participation rates. Meanwhile, the independent variables which are
both insignificant for the three models include gross enrollment rate
and school participation rate.