• It is essential that a realistic performance assessment is
kept separate from performance assessment based on
payment.
• It is appropriate to design and replace exams in which
intelligence and capabilities such as report writing and
basic banking information can be measured.
• It is proposed that training sessions should be held for
interviewees before conducting interviews.
• It is appropriate to record the details of interviews and
scores in separate databases.
• It is better to define a coefficient for each course of the
entrance exam.
• It is essential to maintain exam information, private
information, job information and performance
information for more detailed assessment in the future.
The continuous update of current databases in organisations
can be considered important for the data mining process. The
process of providing and maintaining data can be improved
by software specialists.
Conclusion
The appropriate and scientific employment of staff selected
on the basis of organisations and companies entrance exams,
especially in service-based organisations, are of crucial
importance. The use of data mining and the discovery
of covert knowledge in these organisations will be very
effective.
In this article, whilst existing approaches to data mining
applied in human source management were reviewed, a
new model with a stress on the best feasible tree or trees
selection appropriate with the data bank was presented. The
status of employees’ upgrades were recognised by using data
mining techniques, the rules and relation between entrance
exam marks and staff situation with job performance. Firstly,
job performance, the private information of employees
in commercial banks and the human indices which were
effective in performance or upgrade were identified by
studying exam databases. In the next step, a suitable model
was designed to address the shortcomings of previous
research by learning from these studies about data mining
and human source performance. Secondly, a data warehouse
was created. With data mining techniques, the data set was
cleansed. In other words, the unsuitable and redundant
variables were removed. After data cleansing, the records
with empty fields were deleted and suitable amounts were
replaced for lost data. Thirdly, with decision tree techniques,
data was classified and analysed and the primary results
were obtained. Finally, the orders which were not obvious
were explained.
In conclusion, the validity and reliability of the rules were
examined and the model for knowledge discovery and
application for personnel selection was presented. As
a result, in a conceptual approach to the most effective
variables, as well as target variables, it was determined that
the ‘performance evaluation’ target variable was not an
• It is essential that a realistic performance assessment is
kept separate from performance assessment based on
payment.
• It is appropriate to design and replace exams in which
intelligence and capabilities such as report writing and
basic banking information can be measured.
• It is proposed that training sessions should be held for
interviewees before conducting interviews.
• It is appropriate to record the details of interviews and
scores in separate databases.
• It is better to define a coefficient for each course of the
entrance exam.
• It is essential to maintain exam information, private
information, job information and performance
information for more detailed assessment in the future.
The continuous update of current databases in organisations
can be considered important for the data mining process. The
process of providing and maintaining data can be improved
by software specialists.
Conclusion
The appropriate and scientific employment of staff selected
on the basis of organisations and companies entrance exams,
especially in service-based organisations, are of crucial
importance. The use of data mining and the discovery
of covert knowledge in these organisations will be very
effective.
In this article, whilst existing approaches to data mining
applied in human source management were reviewed, a
new model with a stress on the best feasible tree or trees
selection appropriate with the data bank was presented. The
status of employees’ upgrades were recognised by using data
mining techniques, the rules and relation between entrance
exam marks and staff situation with job performance. Firstly,
job performance, the private information of employees
in commercial banks and the human indices which were
effective in performance or upgrade were identified by
studying exam databases. In the next step, a suitable model
was designed to address the shortcomings of previous
research by learning from these studies about data mining
and human source performance. Secondly, a data warehouse
was created. With data mining techniques, the data set was
cleansed. In other words, the unsuitable and redundant
variables were removed. After data cleansing, the records
with empty fields were deleted and suitable amounts were
replaced for lost data. Thirdly, with decision tree techniques,
data was classified and analysed and the primary results
were obtained. Finally, the orders which were not obvious
were explained.
In conclusion, the validity and reliability of the rules were
examined and the model for knowledge discovery and
application for personnel selection was presented. As
a result, in a conceptual approach to the most effective
variables, as well as target variables, it was determined that
the ‘performance evaluation’ target variable was not an
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