İşgören Seçiminde İnsan Kaynakları Analitiği (İKA) Yaklaşımının Kullanılması
The Use of Human Resources Analytics Approach in Employee Selection

Summary/Abstract: Purpose – The main purpose of this study is to show how human resources analytics methods can be applied in classification prediction for the selection of employees on a case to fill the gap in the national literature. Design/methodology/approach – Random Forest, GBT, logistic regression, KNN and Naive Bayes methods were used among the classification prediction methods. The classification labels of employee candidates were estimated using the gradient incremental decision tree method. Findings – It has been observed that the afore mentioned methods gave close results on a case-bycase basis. The relative weights of the employee selection criteria were obtained by choosing the GBT method. For the R&D department appliciants' suitability, while general aptitude test has been the most significative criteria; reference channel, number of certificates, gender and the education level have not made a serious distinction. Discussion – It is seen that the results obtained in employee selection are similar to the ones in international literature. The modelling made with the attributes selected, the criteria of employee selection affects the classification success in various weight and the criteria are located in accordance with the nature of the R&D department. However, it is evaluated that by using the HR datasets of the companies in Turkey, further studies can be done on the appearance of the employee selection process in the context of Turkey.

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