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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Yeferzon Meza-Chaupis
Universidad Nacional de Educación Enrique Guzmán y Valle

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Vector support machine algorithm applied to the improvement of satisfaction levels in the acquisition of professional skills Omar Chamorro-Atalaya; Orlando Ortega-Galicio; Guillermo Morales-Romero; Darío Villar-Valenzuela; Yeferzon Meza-Chaupis; César León-Velarde; Lourdes Quevedo-Sánchez
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp597-604

Abstract

The study carried out identifies the metricss of the predictive model obtained through the support vector machine (VSM) algorithm, which will be applied in the satisfaction of the acquisition of professional skills of the students of the Professional Engineering Career. As part of the development, the statistical classification tool is used, during the development of the research, it was identified that the predictive model presents as general metrics an accuracy of 82.1%, a precision of 70.72%, a sensitivity of 91.06% and a specificity of 87.60%. Through this model, it contributes significantly to decision-making in relation to improving satisfaction related to the acquisition of professional skills in engineering students, since decision-making by university authorities will have a scientific basis, to take early and timely actions in relation to the predictive elements.
Co-Authors César León-Velarde Darío Villar-Valenzuela Guillermo Morales-Romero Lourdes Quevedo-Sánchez Omar Chamorro-Atalaya Orlando Ortega-Galicio