Automation of Control of Personnel Activities

The graduation paper "Automation of control of personnel activities" deals with the application of automation based on fuzzy inference system for the classification of employees into three groups by their conformity to schedule. This classification will allow to easily and quickly analyze weaknesses in the supervision of the staff, to take appropriate measures and to base the incentive system on the results. The aim of this work is to automate the monitoring of staff clock in and clock out times. To achieve this goal the following tasks were solved: 1. Explore modern methods of control of staff clock in and clock out times. 2. Analyze the classification methods used in conditions of uncertainty. 3. Build classifying fuzzy inference model. 4. Test the efficiency of the model on real data. The work analyzes significance of control for organizations, formulates the basic terms of the efficiency of control systems. The market solutions to control working time in the computer and non-computer organizations were studied. Among mathematical apparatus, which are used to solve classification problems under uncertainty, fuzzy inference has been chosen. So, the mathematical model was developed and implemented by means of Matlab. Finally, fuzzy inference system was tested on real data. The paper contains three chapters. The first chapter discusses the theoretical foundations of personnel control, provide the review of existing solutions of the problem and examine the mathematical tools used to solve classification problems under uncertainty. In the second chapter, a formal statement of the problem in the terms of fuzzy logic and fuzzy inference systems is given. Moreover, this chapter covers the process of model developing. In the last chapter the model is being tested on real data and the results were studied.