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

Salazar Marín Gloria, Condori Obregon Patricia, Palomino Vidal Carlos


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.


Human resource allocation; Linear regression; Logistic regression; Machine learning; Support vector machine

Full Text:




  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics