DSS for Selection of Exemplary Employees Using the Simple Additive Weight (SAW) Method

Ariandi, Vicky and Ikhlas, Muhammad and Afira, Riandana (2020) DSS for Selection of Exemplary Employees Using the Simple Additive Weight (SAW) Method. JURNAL IPTEKS TERAPAN, 14 (4). pp. 442-448. ISSN 2460-5611

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Abstract

Anagement of human resources (HR) from an office affects many aspects that determine the success of the work of the Village Office. One of the most important things in HR management in an office is the selection of the best employees to spur employee morale in improving their dedication and performance. However, in reality, the Manggung Village Office has not been optimal in the implementation of the selection of the best employees, this is due to the unavailability of media that processes employee assessments and provides recommendations in selecting the best employees. The Decision Support System can adjust to the Manggung Village Office in optimizing the selection of the best employees. The purpose of this research is to produce the best employee information based on the needs of the Manggung Village Office. Decision Support Systems are part of computer-based information systems including knowledge-based systems or knowledge management that are used to support decision making in an organization or office. The method used is Simple Additive Weighting (SAW), the calculation of this method is to use the result of the largest value that will be selected as the best alternative, the calculation will be appropriate if the selected alternative meets the predetermined criteria. This decision support system for selecting the best employee was developed using the PHP programming language (Hypertext Processor File), as well as the MySQL database as the database server. The results of this study indicate that the best employee ranking with the highest score

Item Type: Article
Uncontrolled Keywords: SAW, best employee, Manggung Village Office
Subjects: 0 Research > Ilmu Komputer > Sistem Penunjang Keputusan
Divisions/ Fakultas/ Prodi: Fakultas Ilmu Komputer
Depositing User: Administrator
Date Deposited: 16 Sep 2021 03:31
Last Modified: 16 Sep 2021 03:31
URI: http://repository.upiyptk.ac.id/id/eprint/3167

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