This Author published in this journals
All Journal Paradigma
Putra, Farhan Nopransyah
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Implementation of the Standard Deviation Multi-Objective Optimization by Ratio Analysis Method in Warehouse Staff Recruitment Selection Putra, Farhan Nopransyah; Priandika, Adhie Thyo
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 2 (2025): September 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i2.8373

Abstract

The warehouse staff selection process has a crucial role in ensuring optimal operational efficiency and logistics management. A selection approach that considers aspects of technical skills, work experience, and compatibility with the organization's culture is essential in ensuring the efficiency and effectiveness of logistics management. The labor selection process, including in the context of warehouse staff recruitment, often faces challenges due to subjectivity in decision-making. The implementation of the SD-MOORA method is the main goal in this study in the process of accepting warehouse staff to improve the objectivity and accuracy of candidate selection, the results of this study are expected to contribute to improving the efficiency of the labor selection process and support data-based decision-making in human resource management. The data used in this study consists of 8 candidates and 6 criteria in the selection of warehouse staff admission. The final outcome of optimizing the SD-MOORA method for ranking warehouse staff admissions shows that GT secured the top rank with a value of 0.3827, indicating it is the most suitable candidate according to the selection criteria. AN followed in second place with a score of 0.3752, and BD placed third with a score of 0.3579. This study significantly contributes to advancing the development of decision support systems for warehouse staff selection by applying the SD-MOORA method. By objectively considering the weighting of criteria using standard deviations, this approach enhances both the accuracy and transparency of candidate rankings.