Human resource optimization using linear regression machine learning model: case study SUNAT

Abstract

The continue searching for organization’s process improvement for reduce cost and increase efficiency is a big challenge for organizations nowdays. This paper is about to recognize the importance of process improvement focusing in the right human resource allocation. The research predict best optime human re- source allocation in the Superintendencia Nacional de Aduanas (SUNAT) in the chemical materials control area using a linear regression machine learning (ML) algorithm. This model was validated with recollected data in the SUNAT’s con- trol locations, the results were compared with historical data to determine their efficiency obtained a mean square error (MSE) 0.434 that is lower comparing to logistic regression and support vector machine algorithm. This research rec- ommend the implementation of this model in all SUNAT’s controls locations in Peru.