Implementasi Artificial Neural Network (ANN) dalam Sistem Pakar Klasifikasi Kandidat Karyawan Baru. (Implementation of Artificial Neural Networks (ANN) in an Expert System for New Employee Candidate Classification)

Maulana Lutfi, Hajir (2026) Implementasi Artificial Neural Network (ANN) dalam Sistem Pakar Klasifikasi Kandidat Karyawan Baru. (Implementation of Artificial Neural Networks (ANN) in an Expert System for New Employee Candidate Classification). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

The recruitment process for new employees is an important stage in a company because it directly affects the quality of human resources produced. However, the process of assessing the suitability of employee candidates is often still carried out subjectively and takes a long time. Therefore, a system is needed that can assist in making objective and accurate decisions. This study aims to implement Artificial Neural Network (ANN) in an expert system to classify the suitability of new employee candidates. The data used in this study is prospective employee data consisting of several assessment variables relevant to the company's needs. The ANN method is used as the main method for classification, while Random Forest is used as a comparison method to evaluate system performance. The results of this study show that the Artificial Neural Network method is able to provide a better level of accuracy in classifying the suitability of new employee candidates compared to the Random Forest method. Thus, the expert system that has been developed is expected to assist companies, especially the HRD department, in determining the suitability of employee candidates more objectively, effectively, and efficiently.

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