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Bulletin of Informatics and Data Science
Published by Asosiasi Peneliti Data Science Indonesia
ISSN : -     EISSN : 25808389     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
The Bulletin of Informatics and Data Science journal discusses studies in the fields of Informatics, DSS, AI, and ES, as a forum for expressing research results both conceptually and technically related to Data Science
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 4 Documents
 1 
Search results for , issue "Vol 3, No 1 (2024): May 2024" : 4 Documents clear
Combination of MEREC and WASPAS Methods for Performance Assessment in the Decision Support System for Member Admission for the Metaverse Team Putra, Ade Dwi; Rahmanto, Yuri; Darwis, Dedi; Aldino, Ahmad Ari; Setiawansyah, Setiawansyah
Bulletin of Informatics and Data Science Vol 3, No 1 (2024): May 2024
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v3i1.100

Abstract

The selection of the right team members is critical to the success of complex and multidisciplinary Metaverse projects, the previous method used in this selection employed criteria weights based on individual evaluator assessments.. This study proposes the application of a combination of MEREC (method based on the removal effects of criteria) and WASPAS (weighted aggregated sum product assessment) methods to build a DSS in the selection of Metaverse team members. The MEREC method is used to determine the weight of relevant criteria, such as technical skills, communication, innovation, problem-solving, team collaboration, and experience. Meanwhile, the WASPAS method is used to rank candidates based on evaluation scores calculated using a combination of the Weighted Sum Model (WSM) and the Weighted Product Model (WPM). The results showed that the candidate with the highest score was Member Candidate 5 with a score of 0.9806, followed by Member Candidate 11 with a score of 0.944 and Member Candidate 9 with a score of 0.9433. This research proves that the combination of MEREC and WASPAS methods can be used effectively to select team members who have the best quality and are in accordance with the needs of Metaverse projects. A major contribution of this research is the development of a more objective and structured method for the selection of team members in technology projects that require multidisciplinary expertise
Selection of the Best Customer using a Combination of Rank Order Centroid and Grey Relational Analysis Arshad, Muhammad Waqas; Rahmanto, Yuri; Setiawansyah, Setiawansyah
Bulletin of Informatics and Data Science Vol 3, No 1 (2024): May 2024
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v3i1.84

Abstract

A customer is an individual or entity that purchases goods or services from a company or organization. They play an important role in business success, as customer satisfaction and loyalty can determine a company's reputation and sustainability in the marketplace. One of the main challenges is collecting and analyzing accurate and comprehensive data regarding purchase behavior, transaction frequency. Other challenges include keeping customer data confidential and ensuring that the selection process is fair and transparent. The ROC method is used in the initial stage to determine the importance weight of each criterion based on the subjective ranking of the decision makers, which is then converted into numerical weights systematically and consistently, the GRA method is applied to calculate the relational proximity between each customer's alternative to the ideal solution based on their performance values on each criterion.The purpose of this study is to develop and implement a comprehensive framework for the selection of the best customers by combining ROC weighting and GRA methods, and provide practical recommendations for companies in managing and utilizing the best customer relationships, in order to improve customer loyalty and long-term profitability. By combining these approaches, businesses can effectively prioritize customers based on their significance and potential to build long-term relationships and maximize profitability, thus enabling more targeted marketing strategies and better resource allocation. The best customer ranking results were obtained by Customer I with a final GRG value of 0.1792 for the 1st rank, Customer D with a final GRG value of 0.1683 for the 2nd rank, and Customer K with a final GRG value of 0.1505 for the 3rd rank
Effectiveness of Weighting in Assessing Ranking Criteria on the SWOT-MAGIQ Matrix Ambarsari, Erlin Windia; Subagio, Relo; Mesran, Mesran
Bulletin of Informatics and Data Science Vol 3, No 1 (2024): May 2024
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v3i1.85

Abstract

The Analytical Hierarchy Process (AHP) has been a prominent tool in decision-making, but the Multi-Attribute Global Interference of Quality (MAGIQ) offers an alternative with its unique weighting mechanism. This research delves into the effectiveness of weighting in assessing ranking criteria within the SWOT-MAGIQ matrix. The study contrasts the traditional Rank Order Centroid (ROC) approach with the Improved Rank Order Centroid (IROC), focusing on their application in the SWOT analysis. While ROC provides simplicity, IROC aims for enhanced accuracy by considering variability in rankings. The results indicate nuanced differences, with ROC assigning higher weights to criteria such as "Friendly Staff" (0.3183 vs. IROC’s 0.3125), while IROC prioritizes aspects like "Strong Customer Relationships" more significantly (0.1103 vs. ROC’s 0.1053). The choice between ROC and IROC hinges on the specific needs of the decision-making context, with IROC potentially offering a more detailed perspective in complex scenarios. This research underscores the importance of selecting the appropriate weighting mechanism to ensure informed and strategic decisions within the SWOT-MAGIQ framework
Implementation of Decision Support System in Choosing the Best E-Wallet using ROC and MOORA Weighting Methods Mesran, Mesran; Qomaini, Ahmad; Sirait, Ika Paulina; Rosnizam, Rosnizam
Bulletin of Informatics and Data Science Vol 3, No 1 (2024): May 2024
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v3i1.87

Abstract

This research aims to analyze digital wallet usage preferences among university students using a decision support system. With the rise of various digital wallet services such as DANA, LinkAja, and GoPay, students often have difficulty in choosing the platform that best suits their needs. To solve this problem, the research uses a combination of the Rank Order Centroid (ROC) and Multi-Objective Optimization by Ratio Analysis (MOORA) methods. The ROC method was used to determine the criteria weights, while MOORA was applied to rank the digital wallet alternatives. The criteria used in this study include merchant range, cashback program, transaction fees, and ease of use. The research sample consisted of 150 students from the Faculty of Economics, Universitas Nusantara. The results showed that GoPay ranked first as the most preferred digital wallet, followed by DANA in second place, and LinkAja in third. The findings are expected to help students in choosing the digital wallet that best suits their preferences, as well as provide input for digital wallet service providers to improve their service quality

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