Diah Sawitri, Aninda Muliani Harahap

Sistem Pendukung Keputusan Menentukan Mutasi Karyawan Menggunakan Metode ORESTE

Introduction

Sistem pendukung keputusan menentukan mutasi karyawan menggunakan metode oreste . Optimalkan mutasi karyawan di PT PLN ULP Labuhan dengan Sistem Pendukung Keputusan metode ORESTE. Tingkatkan kinerja & efisiensi transfer karyawan secara otomatis.

Abstract

Employee transfer is one aspect that influences employee performance in a company. PT PLN (Persero) ULP Labuhan is one of the agencies or companies that implement transfers with the aim of improving employee performance. With the increasingly advanced development of technology, every company is competing to keep up with the times. Employee transfers at PT PLN (Persero) ULP Labuhan are still carried out manually and decisions are made only based on individual or group opinions. Therefore, determining which employees will be transferred takes a long time and produces less than optimal results. This study aims to help PT PLN (Persero) ULP Labuhan identify employee transfers that will provide maximum results. In this study, the waterfall model was applied to build a system that includes the stages of analysis, design, implementation, and testing. This research stage was carried out by collecting data through interviews. The data is then input into a decision support system, calculated using the ORESTE method, and stored in a database. This allows decision making with the final results sorted by system from the smallest to the largest value. The results of the study based on the ORESTE method are that Rizka Utami's alternative is the first alternative with a final value of 6.82211. This is because Rizka Utami's alternative meets almost all criteria starting from Performance Assessment, Organizational Needs, Education and Training, Length of Service and Age.

Review

This paper, titled "Sistem Pendukung Keputusan Menentukan Mutasi Karyawan Menggunakan Metode ORESTE," addresses a pertinent issue in human resource management: the subjective and often inefficient process of determining employee transfers. The authors effectively identify a common problem at PT PLN (Persero) ULP Labuhan, where manual decision-making leads to prolonged processes and sub-optimal outcomes. By proposing a Decision Support System (DSS) that leverages the ORESTE method, the study aims to inject objectivity and efficiency into this critical organizational function, thereby influencing employee performance positively. The research presents a practical application of a multi-criteria decision-making approach to a real-world human resources challenge, offering a tangible step towards more data-driven management. The strength of this work lies in its clear identification of a practical problem and the application of a structured methodology to address it. The ORESTE method is employed to systematically evaluate employee transfer candidates based on multiple criteria, including Performance Assessment, Organizational Needs, Education and Training, Length of Service, and Age. The choice of the Waterfall model for system development ensures a logical progression from analysis to implementation and testing, providing a robust framework for system creation. The abstract clearly outlines the data collection through interviews and the computational process, culminating in a prioritized list of alternatives, demonstrated by the specific finding for Rizka Utami. This application within PT PLN (Persero) ULP Labuhan provides a concrete example of the system's potential utility. While the abstract provides a good overview, the full paper would benefit from a more detailed justification for selecting the ORESTE method specifically, perhaps discussing its advantages over other MCDM techniques in this particular context. Further elaboration on the validation phase, beyond just identifying the top alternative, such as user acceptance testing or a comparison with expert decisions, would also enhance the study's impact. Nevertheless, this research offers a valuable contribution to the field of Decision Support Systems in human resource management. It successfully demonstrates a practical approach to improving decision-making quality and operational efficiency in employee transfer processes, laying a foundation for future exploration into its scalability and broader applicability across diverse organizational settings.

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