Decision Support System for Personnel Selection
Ramil G. Lumauag
Ramil G. Lumauag, Information Technology Department, Iloilo Science and Technology University Miagao Campus, Miagao, Iloilo, Philippines.
Manuscript received on 06 April 2019 | Revised Manuscript received on 12 May 2019 | Manuscript published on 30 May 2019 | PP: 177-179 | Volume-8 Issue-1, May 2019 | Retrieval Number: A2998058119/19©BEIESP
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Abstract: Personnel selection is one of the most critical functions of Human Resource Management (HRM). Apart from the straightforward fact that an organization should be staffed with the right people, a wrong hiring decision can lead to serious consequences. This is one of the important decisions of the management on which the organizational development depends. This research aims to develop a decision support model for personnel selection by applying the C4.5 Decision Tree Algorithm. The decision support model was implemented by simulating the 110 applicants record and it was evaluated in terms of accuracy, error rate, precision and recall. The result of the evaluation revealed that the model has 98.4% accuracy, 1.4% error rate, 98.5% precision, and 98.7% recall which implies that it can provide an accurate and reliable result and valid to be used for supporting decisions. The Decision Support System for Personnel Selection is an innovative tool for human resource management specifically for recruitment and personnel selection that can help analyze complex data for decision-making process.
Index Terms: C4.5 Decision Tree, Data Mining, Decision Support System, Human Resource Management, Personnel Selection

Scope of the Article: Data Mining