N. Sánchez, Daniel Esteban Casas-Mateus, Luz Deicy Alvarado Nieto
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Sánchez, Daniel Esteban Casas-Mateus, Luz Deicy Alvarado Nieto","doi":"10.16925/2357-6014.2020.02.03","DOIUrl":null,"url":null,"abstract":"Introduction: This article is the result of research entitled the behavior of employability indicators in university graduates, developed at the Universidad Distrital Francisco José de Caldas in 2019. \nProblem: The Emple-AP project promotes the creation of an observatory for labor insertion and the strengthening of employability in countries of the Pacific Alliance (PA), which particularly benefits Colombia, because one of its objectives with the PA is to overcome the socioeconomic inequality that exists among its inhabitants. \nObjective: To identify the relationship between employability indicators through classification methods used in Artificial Intelligence. \nMethodology:The indicators’ behavior description involves data pre-processing, a formal global study in statistics and a specific formal study through comparison of classification methods. \nResults: Descriptions of these employability indicators show characteristics of the situation in the studied population. \nConclusion:Given the analysis of the classification model, it is determined that the diversity and disparity of the dataset makes the RandomTree model the most accurate in this research, finding that the system has characteristic behaviors of an adaptative complex system. \nOriginality:Through this research, employability indicators were analyzed through data mining tools, additionally the analysis presented in this article could be replicated under particular conditions in other countries of the PA. \nLimitations:The information comes from the Universidad Distrital Francisco José de Caldas graduate’s office. 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Behavior of employability indicators in university graduates
Introduction: This article is the result of research entitled the behavior of employability indicators in university graduates, developed at the Universidad Distrital Francisco José de Caldas in 2019.
Problem: The Emple-AP project promotes the creation of an observatory for labor insertion and the strengthening of employability in countries of the Pacific Alliance (PA), which particularly benefits Colombia, because one of its objectives with the PA is to overcome the socioeconomic inequality that exists among its inhabitants.
Objective: To identify the relationship between employability indicators through classification methods used in Artificial Intelligence.
Methodology:The indicators’ behavior description involves data pre-processing, a formal global study in statistics and a specific formal study through comparison of classification methods.
Results: Descriptions of these employability indicators show characteristics of the situation in the studied population.
Conclusion:Given the analysis of the classification model, it is determined that the diversity and disparity of the dataset makes the RandomTree model the most accurate in this research, finding that the system has characteristic behaviors of an adaptative complex system.
Originality:Through this research, employability indicators were analyzed through data mining tools, additionally the analysis presented in this article could be replicated under particular conditions in other countries of the PA.
Limitations:The information comes from the Universidad Distrital Francisco José de Caldas graduate’s office. A single source generates a limitation in the data and in the population studied.