C4.5 Algorithm Testing for Recruitment of Prospective Employees at AMIK MEDICOM
Keywords:
Algorithm C4.5, Prediction, Decision Tree, Data MiningAbstract
Testing the C4.5 algorithm for recruiting prospective employees at AMIK MEDICOM is research that aims to identify the effectiveness and suitability of the C4.5 algorithm in the selection process for prospective employees at AMIK MEDICOM, a higher education institution in the field of information and communication technology. The research method uses historical data on recruitment of prospective employees as well as selection criteria set by AMIK MEDICOM. The C4.5 algorithm is used to build a classification model based on the characteristics and qualifications of prospective employees. Testing is carried out by comparing the prediction results from the C4.5 model with actual acceptance decisions, using evaluation metrics such as accuracy, precision, recall, and F1-score. It is hoped that the results of this research can provide recommendations regarding the use of the C4.5 algorithm in supporting the selection process for prospective employees in higher education institutions, as well as implications for increasing efficiency and objectivity in the workforce recruitment process.
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