Algorithm for the Identification of Student Desertion

The purpose of the research was to determine how the logistic regression algorithm influences the identification of student desertion at the University for Andean Development in 2019.The research work has a predictive level of investigation. Surveys were used to a population of 203 students and a sample of 133 students of the first cycle of all study programs of the university.According to the results obtained when implementing the model regarding the personal factors dimension, 11.28% mentioned that they never had family type incidences to make the decision to abandon their studies, on the contrary, 23.16% always mentioned that they always did; as for the Academic Factors dimension, 16.24% mentioned that they never had family type incidences to make the decision to abandon their studies, on the contrary, 23.16% always mentioned that they never had family type incidences to make the decision to abandon their studies. 24% mentioned that they never had academic incidences, which led them to make the decision to abandon their studies and 7.97% always; according to the results obtained with respect to the Socioeconomic Factors dimension, 8.27% of the students stated that they never had social and economic incidences to abandon their studies and 6.02% always had incidences.

Autorentext

Mg. Hasem Enrique Curi Villanueva, maestros en gestión de tecnologías de la información y la comunicación, docente universitario con mas de 5 años de experiencia.Dr. Rafael Wilfredo Rojas Bujaico, docente uniersitario con más de 10 años de experiencia.Mg. Carlos Valqui Castañeda, docente universitario con más de 10 años de experiencia.