PENERAPAN ALGORITMA C4.5 PADA APLIKASI PREDIKSI PENERIMAAN CALON PEGAWAI BARU PT. AERO SYSTEMS INDONESIA
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
PRIMASARI, MEIDA INTAN
Siregar, Riki Ruli A
Kuswardani, Dwina
Siregar, Riki Ruli A
Kuswardani, Dwina
Subject
Teknik Informatika
Datestamp
2022-09-22 07:12:20
Abstract :
The process of receiving new employee candidates in a company is a work that requires professional, targeted and precise ways in order to get competent workforce and improve the quality and success of a company. Constraints are often found in the recruitment process: it's difficult to determine which applicants meet the criteria to become prospective employees in the midst of several candidates, in accordance with the needs of the company, while the number of prospects should be limited. The number of variables or conditions used as support to the decision of acceptance makes the selection and classification process more difficult. To determine candidates who meet the needed criteria and the right recommendations, Algorithm C4.5 is a recommended method that can analyse data in large quantities. This paper presents an application that implements the decision tree with Algorithm C4.5. The data used is "new and prospective employee website"-based data. The achieved result is an application of the prediction pattern of acceptance of new employee candidates with an accuracy of 96%, whose Implementation can assist Human Resource Development (HRD) staff in the selection and acceptance of prospective employees.
The process of receiving new employee candidates in a company is a work that requires professional, targeted and precise ways in order to get competent workforce and improve the quality and success of a company. Constraints are often found in the recruitment process: it's difficult to determine which applicants meet the criteria to become prospective employees in the midst of several candidates, in accordance with the needs of the company, while the number of prospects should be limited. The number of variables or conditions used as support to the decision of acceptance makes the selection and classification process more difficult. To determine candidates who meet the needed criteria and the right recommendations, Algorithm C4.5 is a recommended method that can analyse data in large quantities. This paper presents an application that implements the decision tree with Algorithm C4.5. The data used is "new and prospective employee website"-based data. The achieved result is an application of the prediction pattern of acceptance of new employee candidates with an accuracy of 96%, whose Implementation can assist Human Resource Development (HRD) staff in the selection and acceptance of prospective employees.
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