Services on Demand
Journal
Article
Indicators
Cited by SciELO
Access statistics
Related links
Cited by Google
Similars in SciELO
Similars in Google
Share
Información tecnológica
On-line version ISSN 0718-0764
Abstract
MOSQUERA, Rodolfo; PARRA-OSORIO, Liliana and CASTRILLON, Omar D. Methodology for Predicting the Psychosocial Risk Level on Colombian Teachers using Data Mining Techniques. Inf. tecnol. [online]. 2016, vol.27, n.6, pp.259-272. ISSN 0718-0764. http://dx.doi.org/10.4067/S0718-07642016000600026.
This paper proposed the application of data mining to identify the psychosocial risk level in teaching elementary, middle y high school education in Colombia. A sample of 1100 data records corresponding to individual assessments were analyzed and processed. The samples were used as input data to the data mining tool called WEKA. Results were compared to assess the performance when applying data mining techniques and classification trees J48 and Naive Bayes. Finally, the application of this predictive tool allows the accuracy 91% compared to the clinic diagnostic. It is concluded that the method can be used tool for preventing the occurrence of psychosocial risk factors in Colombian public school teachers.
Keywords : Psychosocial risk factors classification; WEKA J48; Colombian teachers; teaching elementary data mining.