Improvisation of Minimax Algorithm with Multi Criteria Decision Maker (MCDM) in the Intelligent Agent of Card Battle Game

Permana, Silvester Dian Handy; Bintoro, Ketut Bayu Yogha; Arifitama, Budi; Syahputra, Ade; Cendana, Maya

doi:10.1109/icecos47637.2019.8984477

Cited by 1 publication

(1 citation statement)

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“…Decision Support System (DSS) is a flexible, interactive, computer-based information system and adaptable, developed to support solutions to problems unstructured specific management. Several studies in the field of a decision support system [1], [2] have been conducted such as for selecting student interest-based on curriculum [3] where an expert system is used as a comparison method to find best alternatives solution, then research in the field of gamification [4] where a multi criteria decision-maker is implemented to improve an artificial agent in immersive mobile technology [5]. In this research, Profile Matching method is used for an employees assessment selection to provide a comparison between the employee's value and the company's standard value [6], [7] and it is also proven able to select the best alternative from several alternatives [8], [9] [10].…”

Section: Introductionmentioning

confidence: 99%

Decision Support System for Rewarding Courier Employees in North Jakarta Using Profile Matching

Nugraha

Arifitama

Yaddarabullah

2021

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Courier employees in an expedition company are an important asset for the company. Each Courier has a daily productivity performance to aim with a perfect score (100%) to gain a reward. However, an assessment based only on productivity performance cause problems, where it is impossible to achieve a perfect productivity score to get a reward. This research focus to improve the rewarding system using a decision support system by adding other aspects than productivity which is the behavioral aspect. Absentee, successful delivery, cash on delivery, status update, attendance, and lateness are the behavioral aspect criteria used. Profile Matching method is conducted to compare employee profiles with the standard values and calculate its GAP. The smaller the GAP, the greater the weight results for the best alternative solution. The results, from 150 employees, 5 employees were selected as the best employees and granted rewards with the highest position scored 4,733, second scored 4,725, third scored 4,7234, fourth scored 4,722, and fifth scored 4,721. Profile matching has proven to be excellent as a method for a decision support system to reward employees based on ranking.

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