Classification and Regression Trees (CART) Algorithm for Employee Selection

Aulia Rahmawati, Rizal Muhammad Affandi, Dea Debora Aprillia, Daffa Maulana, Zudha Pratama, Moch. Sjamsul Hidajat

Abstract


Recruitment is the main key in an effort to improve the quality of human resources in a company. Good or bad employees greatly affect the quality of the company. Therefore, it is necessary to be thorough and take a long time in screening applicants in order to get competent, professional and as expected prospective employees. The absence of professional staff to conduct employee selection is the background of this research. So the researcher uses the CART algorithm for the classification of employee recruitment, so it is hoped that it can help companies in conducting employee selection. The dataset was obtained from the selection of freelance daily workers at the Pati Regency Civil Service Police Unit in 2018, totaling 290 prospective employees. Based on calculations on 5-fold cross validation, the resulting accuracy is 98.27%, precision is 99.13% and recall is 96.88%.

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References


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DOI: https://doi.org/10.33633/jais.v7i3.7201

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Journal of Applied Intelligent System (e-ISSN : 2502-9401, p-ISSN : 2503-0493) is published by Department of Informatics Universitas Dian Nuswantoro Semarang and IndoCEISS.

  

 

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