Aplicação de técnica da mineração de dados na identificação do perfil de empregados absenteístas e presenteístas em uma empresa de courier da cidade de São Paulo

Abstract

Professional development, coupled with the organizations and the pressure to achieve goals more daring, leave employees overwhelmed. They end up getting some disturbance in health related to work activity, which can lead to absenteeism or presenteeism. Absenteeism is not reporting to work or social obligations, as scheduled. In the case of presenteeism is the presence of the employee at work or social obligations, though ill, however, their activities are unproductive. Both are similar with regard to loss of productivity. For the company this means that a service is no longer provided due to lack of employee or is performed improperly. More specifically, for the Courier company, where the main activity is the delivery of express shipments, absenteeism and presenteeism affect the quality of these services. To identify these phenomena, this study used a data mining technique called artificial neural network-type Self-Organizing Map of Kohonen (Self-Organizing Map) or simply SOM the to mine data from a database with 740 records of 36 employees Courier firm the city of Sao Paulo. The SOM was used to group employees by similarity of their attributes in order to verify the possible profile and absenteeist or presenteeist also present in them and a possible tendency to acquire these profiles. Also a survey was conducted with the same the with 36 employees to verify the occurrence of stress in employees, and therefore considered essential to present profile absenteeist and presenteeist. The results presented by SOM showed that application of data mining to identify and profile absenteeist and presenteeist in a Courier company in São Paulo is satisfactory, which confirms the use of this technique as a good option to be applied in such problem.