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La depresión de los estudiantes es un tema importante para la mayoría de las instituciones de educación superior. Aunque este problema ha sido investigado por muchos investigadores que utilizan técnicas de análisis estadístico y de minería de datos, este documento se centró en el rendimiento de las técnicas de depresión de las redes de neuronas artificiales y de árboles de clasificación entre estudiantes de Tecnología de la Ingeniería en la Universidad de Kuala Lumpur (UniKL) Instituto Malasio de Tecnología de la Información ( MIIT). Se identificaron varios factores que pueden influir en la depresión de los estudiantes. Factores de estrés, factores sociales (interpersonales e intrapersonales), factores ambientales y factores demográficos atribuidos para predecir la depresión de los estudiantes. Se comparan los rendimientos de estas técnicas, en función de la precisión. A partir de los resultados del análisis, se encontró que el estrés intrapersonal social contribuyó significativamente a la depresión de los estudiantes. Los rendimientos de ambos métodos se compararon mediante análisis de validación cruzada. La red neuronal artificial tiene la menor tasa de error y la más alta precisión; por lo tanto, la red neuronal artificial es la mejor técnica para clasificar en este conjunto de datos.Citas
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