Author: mag. Mojca Bernik

Mentor: prof. dr. Vladislav Rajkovič






Thesis describes the methodology and usage of human resource management data mining. The human resource management is an important element in the strategic organization management. It is important that the human resource management is integrated in the organizations business strategy and thus enables optimal decision making in the human resource management field.


We define the management according to the level of leadership and management, the demands and activities of human resource management within a modern organization, where the need to include human resource management in the executive management is evident in various models. To support this, the human resource management data information system serves as a basis for the manager’s decision making and knowledge management and data mining play a special part. The data mining methods can be integrated in the human resource management information system. With their help one can explain the existing human resource processes, predict or classify the data and thus support the human resource management decisions. This gives the human resource information a new dimension and enables new knowledge and information to be found in the existing data.


We present and example of usage of the data mining method when analysing the reasons for absenteeism as one of the prominent problems in human resource management. Absenteeism has a negative connotation in every organization as is influences the flow of work and causes extra expenses in the human and other resources reorganization efforts. Therefore knowing the reasons behind it can help us enforce the right measures to counter absenteeism. Using the Weka data mining application we built decision models that not only display the strongest reasons for absenteeism but also help us explain them. The use of data mining is not limited to absenteeism only, but allows data mining in all human resource management and other processes.


Keywords: human resource management, human resource management processes, human resource management information system, decision making processes, knowledge management, data mining