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All Journal Jurnal Masyarakat Informatika Jurnal Buana Informatika Bulletin of Electrical Engineering and Informatics JUTI: Jurnal Ilmiah Teknologi Informasi JUSIFO : Jurnal Sistem Informasi Format : Jurnal Imiah Teknik Informatika JOIV : International Journal on Informatics Visualization Tech-E Jurnal Ilmiah FIFO Jurnal CoreIT BAREKENG: Jurnal Ilmu Matematika dan Terapan JITK (Jurnal Ilmu Pengetahuan dan Komputer) Technomedia Journal Riau Journal of Empowerment IJID (International Journal on Informatics for Development) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) KOMPUTIKA - Jurnal Sistem Komputer Jurnal Manajemen Informatika Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Tekno Kompak Building of Informatics, Technology and Science Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer IJAIT (International Journal of Applied Information Technology) Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi Indonesian Journal of Electrical Engineering and Computer Science Jurnal Sisfotek Global Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Teknik Informatika (JUTIF) Teknika JiTEKH (Jurnal Ilmiah Teknologi Harapan) Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Ilmiah Infrastruktur Teknologi Informasi Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer Reputasi: Jurnal Rekayasa Perangkat Lunak EXPLORER J-Intech (Journal of Information and Technology) BEES: Bulletin of Electrical and Electronics Engineering Jurnal Sisfotek Global Jurnal Telematics and Information Technology (TELEFORTECH) Bulletin of Data Science Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA) Jurnal Pengabdian Masyarakat Inovasi Paradigma Journal of Engineering and Information Technology for Community Service Journal of Computing and Informatics Research JEECS (Journal of Electrical Engineering and Computer Sciences) Jurnal Ilmiah Informatika dan Ilmu Komputer Journal of Informatics, Electrical and Electronics Engineering TEKNOSIA Jurnal INFOTEL Bulletin of Informatics and Data Science Jurnal Ilmiah Computer Science CHAIN: Journal of Computer Technology, Computer Engineering and Informatics Journal of Data Science and Information System Journal of Artificial Intelligence and Technology Information Journal of Information Technology, Software Engineering and Computer Science Jurnal Media Jawadwipa Bulletin of Artificial Intelligence International Journal of Informatics and Data Science Journal of Decision Support System Research Journal of Information Technology Jurnal Informatika
Setiawansyah Setiawansyah
(Scopus ID : 57446859700), Universitas Teknokrat Indonesia
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Comparative Analysis of Objective Weighting Methods and TOPSIS in Multi-Criteria Decision Making Junhai Wang; Setiawansyah Setiawansyah; Pritasari Palupiningsih; Meilia Nur Indah Susanti
JUSIFO : Jurnal Sistem Informasi Vol 12 No 1 (2026): June
Publisher : Information System Study Program, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v12i1.34387

Abstract

Objective weighting methods can produce different criterion priorities and may consequently alter TOPSIS rankings. This study compares RECA, G2M, and LOPCOW within a common TOPSIS framework using a supplier performance dataset comprising seven suppliers and six benefit criteria. Each weighting method was applied to the same decision matrix, and the resulting supplier rankings were evaluated against a reference ranking using Spearman’s rank correlation coefficient. RECA produced a moderately balanced weight distribution, G2M generated nearly uniform weights, and LOPCOW yielded the most differentiated pattern, assigning greater importance to availability, communication, and responsiveness. RECA–TOPSIS and G2M–TOPSIS generated identical rankings and each achieved a Spearman coefficient of 0.9643, whereas LOPCOW–TOPSIS obtained 0.8571 and produced more shifts among middle-ranked suppliers. The findings show that distinct objective weighting mechanisms can substantially change criterion weights while preserving broadly similar ranking structures within the analyzed case. These results should be interpreted as case-specific rather than as evidence of general methodological superiority.
Decision Support System for Selecting the Best Restaurant Waiter Using a Combination of WENSLO Weighting and AROMAN Methods Riska Aryanti; Junhai Wang; Agung Deni Wahyudi; Setiawansyah Setiawansyah; Dedi Darwis
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 2 (2025): December
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.
Decision Support System for Selecting the Best Outsourcing Employee Using CRISUS and WASPAS Setiawansyah Setiawansyah
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 11 No. 1 (2026): June
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v11i1.4

Abstract

The outsourcing employee selection process often faces problems such as high subjectivity in assessments, the involvement of multiple criteria with varying levels of importance, and inconsistencies in decision outcomes when using conventional methods. However, most previous studies still use weighting approaches that are subjective or have not integrated methods capable of optimally improving the objectivity and stability of decision results. These conditions have the potential to result in suboptimal employee selection that does not fully reflect the organization's needs. Based on these issues, this study proposes a Decision Support System for selecting the best outsourcing employees by combining the CRISUS method to objectively determine the criteria weights and the WASPAS method as a tool for evaluating and ranking alternatives. Data is collected through performance assessments based on a number of relevant criteria, and then the criteria weights are calculated using the CRISUS method to proportionally reflect the importance level of each criterion. Next, the WASPAS method is used to calculate the final preference values and generate the employee ranking order. The study results show that Employee A8 ranks first with a preference value of 1.00000, followed by Employee A3 in second place with a value of 0.96951, and Employee A5 in third place with a value of 0.94115. These findings indicate that the integration of CRISUS and WASPAS can produce rankings that are objective, consistent, and easy to interpret, so the proposed system can serve as an effective and reliable decision support tool in the outsourcing employee selection process.
Modification of the Weighted Product Model: Towards a Fairer and More Rational Ranking Adhie Thyo Priandika; Permata Permata; Sumanto Sumanto; Setiawansyah Setiawansyah
IJID (International Journal on Informatics for Development) Vol. 15 No. 1 (2026): IJID JUNE
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2026.6163

Abstract

The weighted product (WP) method is one of the popular methods in decision support systems (DSSs) due to its simplicity, calculation efficiency, and ability to handle various types of criteria with different weights. This research proposes a modification to the WP model designed to enhance fairness and rationality in the ranking process of alternatives. Therefore, a modified approach, Weighted Product with Averaging and Mean-Normalized Evaluation (WP-A), is adopted by integrating objective weighting methods and more adaptive normalization, so that each criterion can be evaluated proportionally. The supplier selection case study is used to test the effectiveness of the proposed model by comparing it with other MCDM methods. The results of the study show that the WP-A method produces more consistent results and has a stronger correlation with other methods, as indicated by Spearman's correlation test, with a value of 0.9828, indicating a very strong level of consistency with the reference rankings. The main contribution of this research is to provide a new framework for the development of the WP method so that it can be relied upon to support a more transparent and objective decision-making system.
The Combination of WENSLO and MUNRA Method in Selecting the Best Employees Based on Multiple Criteria Junhai Wang; Setiawansyah Setiawansyah; Adhie Thyo Priandika; Dedi Darwis; Ari Sulistiyawati
Journal of Computing and Informatics Research Vol 5 No 2 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v5i2.2472

Abstract

This study examines the application of a combination of the WENSLO and MUNRA methods in selecting the best employees based on various criteria to address issues of subjectivity and instability in employee rankings that often arise when data is heterogeneous and criteria are conflicting. The WENSLO method is used to assess and prioritize criteria through structured and preference-based weighting, while MUNRA plays a role in consistently normalizing data and calculating weighted scores for each alternative. The integration of these two methods allows for a more objective evaluation, reduces subjective bias, and produces stable employee rankings even in the presence of data variations or conflicting criteria. The Employee Ranking results show that the top-performing employee is Lestari with a score of 1.3092, followed by Susilo with a score of 1.3080 and Maharani with a score of 1.3003, indicating superior and relatively balanced performance. These findings confirm that the combination of WENSLO and MUNRA can produce clear, objective, and effective employee rankings, as well as provide an adaptive framework to support strategic human resource management.
An Entropy-Assisted COBRA Framework to Support Complex Bounded Rationality in Employee Recruitment Raditya Rimbawan Oprasto; Junhai Wang; A Ferico Octaviansyah Pasaribu; Setiawansyah Setiawansyah; Riska Aryanti; Sumanto Sumanto
Bulletin of Computer Science Research Vol. 5 No. 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i3.505

Abstract

In the employee recruitment process, decision-making often involves many criteria and relies on the subjective judgment of the decision-maker. The main problem lies in how to develop a decision support system that can overcome this complexity while maintaining rationality and objectivity. This study aims to apply a hybrid framework based on the entropy and COBRA methods to support objective decision-making in the employee recruitment process, and to overcome the limitations of subjectivity and bounded rationality in candidate selection with a structured data-driven approach. The entropy method is used to objectively determine the weight of criteria based on data variations, thereby helping to reduce subjectivity in decision-making and increase the rationality of COBRA analysis results. The results of the final calculation using the Entropy-COBRA method, were ranked nine candidates based on their final scores which reflected relative proximity to the ideal solution in the recruitment process. The candidate with the lowest score is considered to be the closest to the ideal solution and has the best overall performance. Raka employees ranked first with a final score of -0.0618, followed by Andra in second place with a score of -0.0597, and Fajar in third place with -0.0357. The results of the final score in the COBRA method with a lower score indicate that an alternative shows superior performance over the other. This framework makes a real contribution to data-driven decision-making for human resource management, particularly in the context of recruitment involving multiple criteria and alternatives.
Decision Support System for Teacher Performance Evaluation Using LODECI Weighting and CODAS Method Fadila Shely Amalia; Muksin Hi Abdullah; Sumanto; Setiawansyah; Junhai Wang
Teknika Vol. 15 No. 2 (2026): July 2026
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v15i2.1476

Abstract

The quality of teacher performance evaluation plays an important role in improving educational outcomes, yet conventional assessment approaches often suffer from subjectivity, inconsistency, and lack of transparent weighting mechanisms. This study proposes a Decision Support System (DSS) model by integrating the LODECI method for objective criteria weighting and the CODAS method for alternative ranking to produce more accurate and data-driven evaluation results. The LODECI method determines criterion weights based on data distribution characteristics, resulting in proportional weights where Classroom Management (0.1881), Pedagogical Competence (0.1825), and Creativity and Innovation (0.1702) are identified as the most influential criteria. Furthermore, the CODAS method evaluates teacher performance using a distance-based approach to the negative ideal solution, producing preference values that enable clear differentiation among alternatives. The ranking results show that A7 – Gina achieves Rank 1 with a value of -0.2399, followed by A3 – Citra in Rank 2 with -0.2181, and A9 – Intan in Rank 3 with -0.1374, indicating their superior performance compared to other alternatives. To ensure robustness, a sensitivity analysis was conducted using 18 threshold (φ) scenarios ranging from 0.1 to 0.95. The results demonstrate that the top-ranked alternatives (A7, A3, and A9) consistently maintain their positions across all scenarios, indicating that the proposed model is stable and not significantly affected by parameter changes. Therefore, the integration of LODECI and CODAS within a DSS framework proves to be effective in producing objective, consistent, and reliable teacher performance evaluations that can support decision-making in educational institutions.
An Integrated Decision Support System Using Respond to Criteria Weighting and Root Assessment Method for Content Creator Selection Temi Ardiansah; Iswan A. Thais; Aditia Yudhistira; Ahmad Ari Aldino; Setiawansyah
Teknika Vol. 15 No. 2 (2026): July 2026
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v15i2.1477

Abstract

This study proposes an integrated decision support system using the RECA Weighting and RAM  methods to improve the objectivity and accuracy of content creator selection in the digital marketing era. The problem addressed arises from the complexity of evaluating multiple candidates based on various criteria such as content quality, engagement, consistency, creativity, and brand alignment, which are often assessed subjectively. The RECA method is applied to determine criteria weights objectively based on data variation among alternatives, while the RAM method is used to rank candidates through normalization, weighting, and root-based transformation to ensure more stable and balanced results. The findings show that the proposed approach is capable of producing consistent and reliable rankings, where the top three alternatives are Nabila Putri as the first rank, followed by Sinta Maharani in second place, and Putri Ananda in third place, indicating their superior performance across all evaluation criteria. Furthermore, sensitivity analysis by adjusting criteria weights by ±0.05 indicates that the ranking results remain relatively stable, demonstrating the robustness of the model. Therefore, the integration of RECA and RAM provides an effective, transparent, and accountable solution for supporting decision-making in content creator selection.
Optimizing Employee Admission Selection Using G2M Weighting and MOORA Method Yuri Rahmanto; Junhai Wang; Setiawansyah Setiawansyah; Aditia Yudhistira; Dedi Darwis; Ryan Randy Suryono
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 1 (2025): March 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i1.8224

Abstract

An objective and effective employee admission selection process is a crucial step for the success of the organization in achieving its goals. Problems in employee recruitment selection often arise due to a lack of good planning and system implementation, namely decisions are often influenced by personal preferences, stereotypes, or non-relevant factors, thus reducing objectivity in choosing the best candidates. Objective selection ensures that candidate assessments are conducted based on measurable, relevant, and bias-free criteria, so that only individuals who truly meet the company's needs and standards are accepted. The purpose of developing an optimal approach in employee admission selection using G2M weighting and MOORA is to create a more objective, efficient, and accurate selection process. This approach aims to integrate the calculation of criterion weights mathematically, such as those offered by G2M, in order to eliminate subjective bias in determining criterion prioritization. The MOORA method of evaluating alternative candidates is carried out through ratio analysis that takes into account various criteria simultaneously, resulting in a transparent and data-driven ranking. The results of the employee admission selection ranking based on the criteria that have been evaluated, Candidate 3 obtained the highest score of 0.4177, indicating that this candidate best meets the expected criteria. The second position was occupied by Candidate 6 with a score of 0.3886, followed by Candidate 9 with a score of 0.3528. This research contributes to the recruitment process, by providing a more reliable, transparent, and less subjective way of selecting the right candidates for the positions that companies need.
Integration of G2M Weighting and MOORA in Accurate Decision Making for Best Alternative Selection Setiawansyah Setiawansyah; Junhai Wang; Pritasari Palupiningsih
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol. 11 No. 2 (2025): December 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

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

Abstract

The goal of the integration of the G2M Weighting and MOORA methods is to produce the best alternative selection decisions that are more accurate and objective. By combining rational criteria weighting through G2M Weighting and alternative evaluation using MOORA, it is hoped that it can reduce bias and increase transparency in decision-making. In addition, this study compares alternative ratings from the application of the MOORA method and other weighting methods. The results of the evaluation and ranking of scholarship recipients using G2M weighting and MOORA, CF candidates managed to occupy the first position with a final score of 0.2727, showing the best performance among all candidates. In second place, UT candidates obtained a score of 0.2630, followed by DF candidates with a score of 0.2445 and SS candidates with a score of 0.2425. This approach makes it a very useful solution in the selection of the best alternatives in a wide range of multi-criteria decision applications. The results of the Spearman correlation test showed that the G2M weighting method had the highest correlation of 0.9879, which showed a very high similarity with the initial rating. The Entropy Weighting and CRITIC methods also showed a strong correlation, of 0.9515 and 0.9636, respectively, although there was slight variation in the alternate sequence. Meanwhile, the MEREC weighting has the lowest correlation of 0.9273, but still shows a very strong relationship. Overall, these results suggest that the G2M method produces rankings consistent with the initial rankings, with variations indicating sensitivity to criterion weighting.
Co-Authors Abhishek R Mehta Ade Dwi Putra Ade Surahman Adi Sucipto, Adi Aditia Yudhistira Aditia Yudhistira Agus Perdana Windarto Agus Wantoro Agustina, Intan Ahdan, Syaiful Ahmad Ari Aldino Ahmad Ari Aldino Ahmad Ari Aldino Ahmad Ari Aldino Ahmad Ari Aldino Ahmadfauzy Alfry Aristo Jansen Sinlae Alita, Debby Amalia, Zahrina Andi Nurkholis Andika, Rio Aniyanti Tafonao An’ars, M. Ghufroni Arfinia Rahma Ari Sulistiyawati Ari Sulistiyawati Ariany, Fenty Arie Qur’ania Arief Budiman Arnilia, Okma Arshad, Muhammad Waqas Arsi Hajizah Asistyasari, Ayuni Ayu Megawaty, Dyah Bustanul Ulum Damayanti Damayanti Damayanti, Damayanti Daniarti, Yeni Daniel Prasetyo Tarigan Deas Andrian Dwijaya Debby Alita Dedi Darwis Dedi Triyanto Desyanti Desyanti Desyanti Dinda Titian Lestari Dodi Siregar Dodi Siregar Dwi Satria, M. Najib Dyah Aminatun Dyah Ayu Megawaty Eko Bagus Fahrizqi Erlin Windia Ambarsari Erliyan Redy Susanto Fadila Shely Amalia Fadila Shely Amalia Fajar Irvansyah Faruk Ulum Faruk Ulum Febrianus Gea Fernando, Yusra Fikri Hamidy Gibtha Fitri Laxmi Hamdan Sobirin, Muhammad Heni Sulistiani Heni Sulistiani Hetty Rohayani Ida Mayanju Pandiangan Imam Ahmad Imam Ahmad Iryanto Chandra Isnain, Auliya Rahman Iswan A. Thais Jeperson Hutahaean Jumaryadi, Yuwan Junhai Wang Junhai Wang Junhai Wang Junhai Wang Junhai Wang Junhai Wang Junhai Wang Junhai Wang Kiki Septiani Kurniawan, Arsy Laurent Nababan Mahendra, Ferdian Jerry Mahesa Raihan Rifqi Mandasari, Berlinda Marzuki, Dwiki Hafizh Megawaty, Dyah Ayu Meilia Nur Indah Susanti Merlin Puspita Sari Mesran Mesran Mesran Mesran Mesran, Mesran Mohammad Taufan Asri Zaen Muhaqiqin muhaqiqin Muksin Hi Abdullah Ni Komang Ratih Kumala Nirwana Hendrastuty Nopri Prayoga Nuari, Reflan Nuralia Nuralia Nurman Fadhlullah nurnaningsih, Desi Nuzuliarini Nuris Octaviansyah, A. Ferico Palupiningsih, Pritasari Parjito Parjito Pasaribu, A. Ferico Octaviansyah Pasha, Donaya Permata Permata Permata, Permata Pramuditya, Andri Prastowo, Kukuh Adi Priandika, Adhie Thyo Pritasari Palupiningsih Pritasari Palupiningsih Pritasari Palupiningsih Purbha Irwansyah, Irsyad Pustika, Reza Putra, Ade Dwi Putra, Rulyansyah Permata Putri Sukma Dewi Putri Sukma Dewi Qadhli Jafar Adrian R Metha, Abhishek Raditya Rimbawan Oprasto Rahmadianti, Fitrah Amalia Rahman, Miftahur Rasli, Roznim Mohamad Reflan Revife Purba Ridha Maya Faza Lubis Rilo Nur Devija Rini Nuraini Riska Aryanti Rizkah Fadillah Rohmat Indra Borman Romadhoni, Randi Roswita Daeli Roznim, Roznim Ruziana binti Mohamad Rasli Ryan Randy Suryono S. Samsugi Safi, Mudar Sahrial Ihsani Ishak Sanriomi Sintaro Saputra, Alvin Setiawan, Dandi Setyani, Tria Sindi Apri Nesya Sinta, Ratna Sari Roma Siti Mahmuda Sitna Hajar Hadad Sofiansyah Fadli Sri Agustiani Br Siburian Subhan Subhan Sufiatul Maryana Sufiatul Maryana Sufiatul Maryana Sumanto Sumanto Sumanto Surahman, Ade Susanto, Erliyan Redy Sussolaikah, Kelik Syaiful Ahdan Temi Ardiansah Temi Ardiansah Tri Widodo Trisnawati, Fika Ulum, Faruk Untoro Adji Very Hendra Saputra Very Hendra Saputra Very Hendra Saputra Wahyudi, Agung Deni Wang, Junhai Waqas Arshad, Muhammad Widiyanti, Adella yasin, ikbal Yohanes Eka Wibawa Yosep Nuryaman Yuliani, Asri Yuri Rahmanto Yusra Fernando