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All Journal Jurnal Masyarakat Informatika Format : Jurnal Imiah Teknik Informatika Jurnal CoreIT KOMPUTIKA - Jurnal Sistem Komputer Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Teknik Informatika (JUTIF) JiTEKH (Jurnal Ilmiah Teknologi Harapan) Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research J-Intech (Journal of Information and Technology) Bulletin of Data Science Paradigma JEECS (Journal of Electrical Engineering and Computer Sciences) Jurnal Ilmiah Informatika dan Ilmu Komputer Bulletin of Informatics and Data Science International Journal of Informatics and Data Science Jurnal Informatika dan Rekayasa Perangkat Lunak
Wang, Junhai
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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.
Comparison of Objective Weighting Methods in SAW and Their Effect on Alternative Ranking Results Wang, Junhai; Setiawansyah, Setiawansyah; Sumanto, Sumanto
Jurnal Masyarakat Informatika Vol 17, No 1 (2026): May 2026 (Ongoing)
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.17.1.78414

Abstract

Determining the weights of criteria is a vital stage in multi-criteria decision making, yet it often suffers from evaluator subjectivity and unstable results when relying on expert judgment. Dependence on human perception may also lead to inconsistencies among criteria, highlighting the need for objective, data-driven approaches to generate rational and measurable weights. This study analyzes and compares six objective weighting methods—Entropy, MEREC, RECA, G2M, LOPCOW, and CRITIC—in the selection of new store locations. Each method applies distinct mathematical principles but shares a common foundation in objective data analysis, free from subjective bias. The findings reveal that criterion S5 consistently receives the highest weight, emphasizing its dominant role in decision outcomes. Using the Simple Additive Weighting (SAW) method, New Store Location 5 ranks first across all weighting techniques, followed by Locations 3 and 8. The Spearman correlation test confirms a high level of consistency among methods, with coefficients of 1 for RECA, G2M, and LOPCOW, and 0.9879 for Entropy, MEREC, and CRITIC. These results demonstrate that objective weighting methods produce stable and reliable evaluations, effectively supporting data-based strategic decision making in multi-criteria contexts.
Hybrid Entropy and CRADIS Method Approach in Decision Support System for Selecting the Best Employees Wang, Junhai; Setiawansyah, Setiawansyah; Saputra, Very Hendra
Building of Informatics, Technology and Science (BITS) Vol 7 No 4 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i4.8985

Abstract

Selecting the right employees is a key factor in improving organizational performance and productivity. However, in many organizations, the employee selection process is still conducted through manual assessments and subjective judgments, which may lead to bias and inconsistent decisions. Therefore, a systematic and objective approach is needed to support the evaluation process. This study integrates the Entropy method and the CRADIS method within a decision support system to determine the best employee candidates. The Entropy method is applied to calculate objective criteria weights based on the variation of information in the data, while the CRADIS method is used to rank candidates according to their proximity to the ideal solution and distance from the anti-ideal solution. The integration of these two methods provides a framework that reduces subjectivity in determining criterion importance and produces more discriminative ranking results. The findings indicate that candidate GF achieved the highest score of 0.6848, followed by EY with 0.6835 and AR with 0.6528, showing that these candidates have performance profiles closest to the defined criteria. In addition, sensitivity analysis using several scenarios of criteria weight changes demonstrates that the proposed model is relatively stable, with an overall ranking consistency of 81.8%, while alternatives AR, DI, and FR show 100% ranking stability. These results indicate that the Entropy–CRADIS approach can improve the accuracy, objectivity, and reliability of employee selection decisions in multi-criteria decision-making environments.
Decision Support System for Evaluating Textile Supplier Performance Based on Weights by Envelope and Slope and Mixed Aggregation by Comprehensive Normalization Technique for Multi-Criteria Setiawansyah, Setiawansyah; Wang, Junhai; Palupiningsih, Pritasari; Maryana, Sufiatul
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 7, No 1 (2026)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v7i1.29131

Abstract

The textile industry is highly dependent on supplier performance in ensuring the quality of raw materials, timely delivery, price stability, and supply continuity. The complexity of supplier evaluation involving many criteria often leads to subjectivity and inconsistencies in decision-making when using conventional approaches. This study proposes a decision support system to evaluate textile supplier performance based on a combination of Weights by Envelope and Slope (WENSLO) and Mixed Aggregation by Comprehensive Normalization Technique for Multi-Criteria (MACONT). The WENSLO method is used to determine the weight of criteria objectively based on data distribution characteristics, while MACONT is applied to assess and rank supplier alternatives through a comprehensive normalization and aggregation process. The case study was conducted involving nine suppliers and five evaluation criteria, namely material quality, timeliness, price, supply capacity, and responsiveness. The results of the study indicate that the proposed model is capable of producing clear and stable supplier rankings, with Supplier A9, Supplier A7, and Supplier A2 occupying the top three positions. These findings demonstrate that the integration of WENSLO and MACONT can enhance the objectivity and consistency of decision-making, as well as provide a more reliable and relevant framework for evaluating textile suppliers to support data-driven supply chain management.
Co-Authors Aditia Yudhistira Alita, Debby Anars, M. Ghufroni Ardiansah, Temi Ari Sulistiyawati Ariany, Fenty Asistyasari, Ayuni Chandra, Iryanto Dedi Darwis Gunawan, Rakhmat Dedi Imam Ahmad Isnain, Auliya Rahman Jumaryadi, Yuwan Megawaty, Dyah Ayu Mesran, Mesran Nirwana Hendrastuty Nuryaman, Yosep Oprasto, Raditya Rimbawan Palupiningsih, Pritasari Pasaribu, A. Ferico Octaviansyah Permata, Permata Putra, Ade Dwi Riska Aryanti Ryan Randy Suryono Setiawansyah Setiawansyah Sitna Hajar Hadad Sufiatul Maryana Sumanto, Sumanto Ulum, Faruk Very Hendra Saputra Wahyudi, Agung Deni Yuri Rahmanto