Time series forecasting of internal student migration using ML-ARIMA model

Abstract

This study employs a machine learning-based predictive approach to assess the trend of internal migration of students from the Northeast region of India between 2011 and 2031. The study uses Census of India migration data from 1981 to 2011 to use the ARIMA model as part of a predictive inferential research approach. This study aims to close the data gap on internal student migration from Northeast India, where there has been a relatively high intensity of educational out-migration. The research predicts that the amount of this migratory stream will keep on rising. The ARIMA model shows a consistent rise in student out-migration from the region. The results point to significant policy ramifications for resolving the region's educational infrastructure shortcomings and lessening the strains imposed by migrants on big urban educational hubs.