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All Journal Internet of Things and Artificial Intelligence Journal
Sihombing, Lasminar Lusia
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Best Employee Selection Using The Additive Ratio Assesment Method Siregar, Victor Marudut Mulia; Sirait, Erwin; Sihombing, Lasminar Lusia; Siregar, Ivana Maretha
Internet of Things and Artificial Intelligence Journal Vol. 3 No. 1 (2023): Vol. 3 No.1 (2023): Volume 3 Issue 1, 2023 [February]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v3i1.589

Abstract

This study aims to solve the problem of selecting the best employees at Café Alvina. In order for employee performance to be further improved and more motivated in doing their work, the leadership gives awards to employees who have a good reputation in it so that all employees are motivated to be able to improve the quality of their respective work. The problem of selecting the best employees is done by building a decision support system. The DSS was built using the ARAS (Additive Ratio Assessment method) method. The criteria used consisted of discipline, responsible, diligent, and cooperation with the weight of each criterion being 0.28, 0.11, 0.19, 0.31, 0.11. The results obtained from this study are the best employee recommendations consisting of employee_004 with a score of 0.9246 ranked 1st, employee_006 with a score of 0.8244, ranked 2nd, and employee_002 with a score of 0.5446 ranked 3rd. Through this decision support system, Alvina's café manager was greatly assisted because it becomes easier to decide on the selection of the best employees at the Café.
Co-Authors Erwin Sirait, Erwin Siregar, Ivana Maretha Siregar, Victor Marudut Mulia