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p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal Bulletin of Informatics and Data Science International Journal of Informatics and Data Science
Ridha Maya Faza Lubis
Southern Taiwan University of Science and Technology
Computer Science & IT Electrical & Electronics Engineering Engineering

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Decision Support System for Determining New Branch Locations Applying the Multi Attribute Utility Theory (MAUT) Method Muhammad Zakaria Lubis; Ruziana; Rizkah Fadillah; Ridha Maya Faza Lubis
International Journal of Informatics and Data Science Vol. 1 No. 1 (2023): December 2023
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The location of new branches that are close to community activities and have adequate facilities makes it easier for consumers to get the services and products they need. Determining the feasibility of new branch locations from several product or service producers still uses a system that is not accurate, which can cause problems in determining the location of new strategic and targeted branches. However, there are several obstacles in the selection of new branch locations, so technological assistance is needed in determining the location, product analysis, marketing management, and other matters concerning the development of the business being carried out. Technology that is considered efficient, easy, and flexible and is used by entrepreneurs, especially in determining the location of new branches using a decision support system using the MAUT method, is expected to help the location of new branches that are efficient and strategic. The decision support system is a conclusion and determination of the best using some data and computerized testing in each criterion so as to get valid results. After calculating each criterion and alternative, the best ranking is obtained in alternative A1 with a value of 0.7925 on Pertahanan Street.
Comparative Analysis of MCDM Methods in Employee Award Ranking Roznim binti Mohamad Rasli; Mesran Mesran; Ridha Maya Faza Lubis
Bulletin of Informatics and Data Science Vol 5, No 1 (2026): May 2026
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v5i1.141

Abstract

Awards are an important form of appreciation for outstanding employees, but the process of selecting recipients is often faced with various challenges, especially in assessing subjective aspects of performance. To overcome this, the Multi-Criteria Decision Making (MCDM) method can be an effective solution. MCDM offers a systematic framework for evaluating various alternatives (in this case, employees) based on a number of relevant criteria. By using the MCDM method, the process of selecting award recipients can be carried out more objectively and transparently. Some commonly used MCDM methods, such as MAUT, OCRA, and CoCoSo, have their own advantages and disadvantages. This study aims to compare the three methods specifically in the context of selecting employee award recipients. The final results obtained show that the best alternative is A6, where the results of the three methods look the same position or location in the ranking. After a comparative analysis of the three methods, it can be concluded that the OCRA method is the best method in terms of ranking consistency compared to the other two methods. Thus, it is hoped that recommendations for the most suitable MCDM method can be obtained to be applied in similar situations
Co-Authors Mesran Mesran Muhammad Zakaria Lubis Rizkah Fadillah Roznim binti Mohamad Rasli Ruziana