Machine Learning Application for Predicting the Waiting Time of Brazilian Federal Public Services

• Vítor G. de Menezes UnB
• Glauco V. Pedrosa UnB https://orcid.org/0000-0001-5573-6830
• Michel A. Ribeiro UnB
• Rejane M. da C. Figueiredo UnB https://orcid.org/0000-0001-8243-7924

DOI: https://doi.org/10.5753/wcge.2021.15981

Abstract

This paper uses machine learning techniques to predict public service waiting times. The waiting time analyzed in this work refers to the period (in days) of the duration from the service request to the actual delivery to the requesting user. This work was developed in cooperation with the Brazilian Government, which conducted an exploratory interview with managers of 289 federal services. Then, a data mining was carried out to identify a set of variables that would allow to predict with high effectiveness the waiting time of a service from its managerial aspects. Two models are presented in this article: a predictive model for services offered to individuals, with an accuracy of 77% and another for companies with an accuracy of 70%.

Keywords: Data Science, Machine Learning, Digital Government

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