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Decision Support System in Determining the Optimal Raw Material Supplier Using a Combination of Entropy and MOORA Wang, Junhai; Ahmad, Imam; Setiawansyah, Setiawansyah
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.006

Abstract

The selection of the right raw material supplier plays a crucial role in ensuring the efficiency and sustainability of supply chain management. However, the decision-making process is often complex due to the multiple criteria that must be considered simultaneously, such as quality, price, delivery timeliness, production capacity, and flexibility. To address this challenge, this study applies a decision support system that integrates the Entropy method for objective weighting of criteria and the MOORA method for ranking alternatives. Entropy weighting provides an unbiased determination of the importance of each criterion based on data variation, while MOORA delivers a systematic ranking of suppliers by combining benefit and cost criteria into a comprehensive performance score. The results of the analysis on eight supplier alternatives show that Supplier S8 achieves the highest ranking, followed by Supplier S3 and Supplier S6, indicating their superior ability to meet the defined criteria, especially in capacity and flexibility. Meanwhile, Supplier S4 ranks the lowest, reflecting its relatively weaker performance across several aspects. These findings demonstrate that the combination of Entropy and MOORA provides a reliable, objective, and transparent framework to support decision-making in supplier selection.
Decision Support System for Performance Assessment of the Best Salesperson with the Integration of Entropy and WASPAS Wang, Junhai; Setiawansyah; Isnain, Auliya Rahman
International Journal of Informatics and Data Science Vol. 2 No. 2 (2025): June 2025
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v2i2.88

Abstract

The salesperson performance assessment is an important aspect of improving the effectiveness of a company's marketing strategy. However, this assessment process often faces the challenge of subjectivity, especially in determining the weights of the criteria used. To address this issue, this study implements a combination of the Entropy and WASPAS methods. The Entropy method is used to objectively determine the weights of the criteria based on data variation, while the WASPAS method is used to evaluate and rank alternatives. A case study was conducted on five salesperson personnel with the criteria used in selecting the best salesperson being sales target achievement, product mastery, communication skills, creativity, and work ethics. The results showed that Muhammad Iqbal (A3) ranked first with a score of 0.882, followed by Andi Saputra (A1) with a score of 0.796, Rizky Kurniawan (A5) with a score of 0.770, Budi Santoso (A2) with a score of 0.724, and Siti Rahmawati (A4) with a score of 0.655. The main contribution of this research is to present a more accurate and objective salesperson performance evaluation model through the integration of the Entropy–WASPAS method. This finding has practical implications for companies in selecting the best employees, identifying salesperson personnel with outstanding performance, and supporting strategic decision-making in human resource development in the marketing field.
Optimization of Production Operator Performance Assessment with Grey Geometric Mean Weighting and Combinative Distance-based Assessment Wang, Junhai; Setiawansyah, Setiawansyah; Ulum, Faruk; Yudhistira, Aditia; Wahyudi, Agung Deni
Komputika : Jurnal Sistem Komputer Vol. 14 No. 2 (2025): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v14i2.15977

Abstract

The performance of production operators plays a crucial role in determining the level of efficiency and effectiveness of the manufacturing process in a company that has a long-term impact on the company's competitiveness. Production operator performance appraisals often face a number of problems that can reduce the accuracy and fairness of evaluations. One of the main problems is the subjectivity of assessment, where evaluation is based more on the personal perception of the supervisor or assessor without a consistently measurable standard. The purpose of this study is to apply a more objective, structured, and accurate production operator performance evaluation model by integrating the grey geometric mean weighting (G2M Weighting) method as an uncertainty-based criterion weighting approach and combinative distance-based assessment (CODAS) as an alternative ranking method. The results of the production operator's performance ranking are that CR Operator ranks first with the highest performance score of 0.7737, GM Operator is ranked second with a score of 0.6187, followed by AN Operator in third place with a score of 0.5895. This research makes a significant contribution to the development of a performance evaluation system in the manufacturing industry environment by integrating the G2M Weighting and CODAS methods as an objective and systematic approach.
Combination of MOORA and ITARA Methods in Decision Support Systems for Measuring the Performance of Quality Control Teams Hendrastuty, Nirwana; Wang, Junhai; Sulistiyawati, Ari; Darwis, Dedi; Setiawansyah, Setiawansyah; Jumaryadi, Yuwan; Sumanto, Sumanto
TIN: Terapan Informatika Nusantara Vol 6 No 6 (2025): November 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i6.8382

Abstract

The problems that often arise in evaluating the performance of the Quality Control team are the subjectivity in determining the weight of criteria and the limitations of traditional methods in producing objective and consistent rankings. To address this issue, this research integrates the Indifference Threshold-based Attribute Ratio Analysis (ITARA) and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) methods within a decision support system. The ITARA method is used to determine the weights of criteria based on data variation, making them more representative of real conditions, with the result that Accuracy of Product Defect Identification becomes the most dominant criterion with a weight of 0.3999, followed by Response Speed to Issues at 0.1877, while other criteria have lower weights. Furthermore, the MOORA method is used to calculate the preference of alternatives, resulting in a final ranking. The analysis results indicate that the Quality Assurance Team ranks first, followed by the Quality Improvement Team in second place, while the Quality Inspection Team is in the last position. To test the reliability of the model, a sensitivity analysis was conducted by varying the weights of the main criteria. The results show that the ranking structure is relatively stable, with changes only occurring in the positions of the first and second ranks when the accuracy weight is reduced by 0.2. In conclusion, the combination of ITARA-MOORA proves to be capable of producing objective, robust, and reliable performance evaluations as a basis for strategic decision-making in enhancing the quality of the quality control teams.
Decision Support System for Video Editing Staff Recruitment Using a Combination of Entropy and Simple Additive Weighting Methods Wang, Junhai; Saputra, Very Hendra; Putra, Ade Dwi; Anars, M. Ghufroni; Pasaribu, A. Ferico Octaviansyah; Ardiansah, Temi
FORMAT Vol 15, No 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2026.v15.i1.006

Abstract

The recruitment process for video editing staff is a strategic stage in ensuring the quality of professional and competitive content production. However, candidate assessment often faces challenges of subjectivity and inaccuracy in decision-making when evaluators rely solely on intuitive judgment without a measured approach. This study aims to develop a decision support system based on Multi-Criteria Decision Making (MCDM) by integrating the Entropy method for objective determination of criteria weights and the Simple Additive Weighting (SAW) method in calculating the preference values of alternatives. Five evaluation criteria are used in the selection process, namely Editing, Creativity, Experience, Discipline, and Teamwork, with the final weights obtained through the Entropy method being 0.2867, 0.2248, 0.2573, 0.0685, and 0.1626. The study results show that the SAW method is capable of processing candidate evaluation scores comprehensively based on these weights, producing final scores that indicate the best candidates, namely Eko Firmansyah (0.986), Indra Mahendra (0.9699), and Candra Wijaya (0.9662) as the three candidates with the highest eligibility. This study demonstrates that the integration of the Entropy–SAW method is effective in creating a selection mechanism that is objective, transparent, and scientifically accountable, thus making a significant contribution to decision-making in the field of human resource management
Decision Support System for Selecting the Best Restaurant Waiter Using a Combination of WENSLO Weighting and AROMAN Methods Aryanti, Riska; Wang, Junhai; Wahyudi, Agung Deni; Setiawansyah, Setiawansyah; Darwis, Dedi
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 2 (2025): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i2.4

Abstract

The quality of service staff is a key factor in determining business success because they are the front line that interacts directly with consumers. However, performance evaluations of service staff are often still carried out subjectively, based only on the supervisor's perception or brief experiences with customers. This research discusses the application of a decision support system to determine the best restaurant service by combining the Weights by Envelope and Slope (WENSLO) method in criteria weighting and the Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN) in the alternative ranking process. The dataset used in this study was collected in 2025 from one of the restaurants in the Lampung area, involving nine waiters as evaluation candidates using six criteria. The six criteria used consist of four benefit criteria: service speed, friendliness, accuracy, and customer satisfaction. The weighting results using the WENSLO method indicate that the order mistakes criterion received the highest weight of 0.7253, followed by completion time with a weight of 0.1700, while the other criteria have relatively small weights. The AROMAN method is used to calculate the final values of alternatives based on the specified weights, resulting in a ranking of restaurant servers. The analysis shows that alternative Waiters KS ranks first with the highest score of 1.6097, followed by Waiters QN and Waiters RB. This finding proves that the combination of the WENSLO and AROMAN methods can produce objective, systematic results, and supports restaurant management in making strategic decisions regarding the selection of the best employees.