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All Journal Jurnal Masyarakat Informatika Bulletin of Electrical Engineering and Informatics JUTI: Jurnal Ilmiah Teknologi 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 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) 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) 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 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 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
Setiawansyah Setiawansyah
(Scopus ID : 57446859700), Universitas Teknokrat Indonesia
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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.
REFORMULATION OF MULTI-ATTRIBUTE UTILITY THEORY NORMALIZATION TO HANDLE ASYMMETRIC DATA IN MADM Puspaningrum, Ajeng Savitri; Susanto, Erliyan Redy; Hendrastuty, Nirwana; Setiawansyah, Setiawansyah
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.7273

Abstract

Multi-Attribute Utility Theory (MAUT) is a widely used multi-attribute decision-making (MADM) method due to its ability to integrate multiple criteria into a single utility value. However, conventional MAUT faces limitations when handling asymmetric data, where standard normalization processes often lead to value distortion and less representative rankings. This study aims to reformulate the normalization function in MAUT to improve adaptability to non-symmetric data distributions and to enhance ranking validity in decision-making. A modification approach called MAUT-A was developed by applying an adaptive normalization mechanism capable of accommodating extreme distributions and outliers by adding Z-score normalization. The performance of MAUT-A was evaluated by comparing the correlation of its ranking results with reference rankings, and the outcomes were benchmarked against conventional MAUT. The experimental findings indicate that conventional MAUT achieved a correlation value of 0.9688 with the reference ranking, while the proposed MAUT-A method achieved a higher correlation of 0.9792. This improvement represents that MAUT-A has better suitability, stability, and reliability in managing asymmetric data. The study contributes by offering a reformulated MAUT framework through adaptive normalization, providing more accurate, stable, and fair ranking outcomes. This approach enhances the validity of MADM applications, particularly in contexts involving asymmetric data distributions
Pelatihan Literasi Digital untuk Guru dan Siswa dalam Meningkatkan Kualitas Pembelajaran Jarak Jauh Windarto, Agus Perdana; Hutahaean, Jeperson; Sussolaikah, Kelik; Setiawansyah, Setiawansyah
Jurnal Pengabdian Masyarakat Inovasi Vol. 5 No. 1 (2026): February 2026
Publisher : Sekolah Tinggi Ilmu Manajemen Sukma Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35126/jpmi.v5i1.998

Abstract

This community service activity aims to improve the digital literacy of teachers and students to support the quality of distance learning. The implementation method was carried out through practice-based training involving 20 participants from among teachers and students. Evaluation results showed that before the activity, the digital literacy level of participants was in the basic to intermediate category with an average score of 1-2, while after the activity there was a significant increase to an average score of 4-5. Participants' satisfaction responses also showed that 80% expressed satisfaction or were very satisfied, confirming the effectiveness of the training. This activity successfully addressed the needs of partners regarding the constraints of low digital competency in online learning, despite the limitations of the limited number of participants and the short duration of implementation. Therefore, this activity is recommended to be expanded and integrated into the ongoing professional development program for teachers and students.
Improving Decision Accuracy Through LOPCOW Weighting and AROMAN Methods in Retail Store Location Selection Setiawansyah Setiawansyah; Yusra Fernando; Agung Deni Wahyudi; Yohanes Eka Wibawa; Nuzuliarini Nuris
Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) Vol. 4 No. 1 (2025): Volume 4 Nomor 1 March 2025
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jima-ilkom.v4i1.57

Abstract

Choosing a strategic store location is an important factor in retail business success, but this decision is often influenced by data uncertainty and scale differences among criteria that can lead to bias in the decision-making process. This study proposes the use of LOPCOW to objectively determine the criterion weights based on data variability among alternatives, and AROMAN to reduce the influence of scale differences among criteria through gradual normalization. With this approach, it is hoped to obtain a more accurate, fair, and consistent ranking of locations. The ranking results in the selection of retail store locations are based on the final value of each alternative location. The location with the code LKM ranks highest with a final value of 0.8212, indicating that this location has the most optimal characteristics compared to other locations. The results of the study show that the combination of these two methods can produce more optimal and reliable decisions in selecting retail store locations, which in turn can enhance competitiveness and operational success in the retail business. The contribution from the ranking results of this retail store location provides significant strategic insights in the decision-making process for business expansion. By leveraging a quantitative approach that generates a final value for each location alternative, this research is able to provide an objective foundation for managers or decision-makers in selecting the best location. The identification of LKM locations as the most superior alternative indicates that the evaluation method used is effective in revealing the competitive advantages of a location based on the established criteria.
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; Junhai Wang; Pritasari Palupiningsih; Sufiatul Maryana
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.
Comparative Analysis of CODAS, TOPSIS, and COCOSO Methods Using Objective Weighting in Multi-Criteria Decision Support Systems Setiawansyah Setiawansyah
Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) Vol. 5 No. 1 (2026): Volume 5 Nomor 1 March 2026
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jima-ilkom.v5i1.78

Abstract

This study aims to objectively assess teachers' pedagogical performance through the application and comparison of three multi-criteria decision-making methods, namely CODAS, TOPSIS, and COCOSO, with the criteria weights determined using the ITARA method. The ranking results show differences in evaluation patterns among the methods, where the CODAS method places Teacher RD in the first rank, followed by Teacher GH and Teacher DG, while Teacher AN is ranked last. In contrast, the TOPSIS and COCOSO methods produced relatively consistent rankings, with Teacher TY ranking first, followed by Teacher AN and Teacher NH in TOPSIS, and Teacher NH and Teacher DG in COCOSO. These differences in results indicate that each method has a different evaluative perspective on the performance of alternatives, depending on the preference calculation approach used. Overall, this comparative analysis confirms that using more than one ranking method can provide a more comprehensive and balanced view in evaluating teachers' pedagogical performance, thereby supporting more accurate and data-driven decision-making.
Co-Authors Abhishek R Mehta Ade Dwi Putra Ade Surahman Adi Sucipto, Adi Aditia Yudhistira Agus Perdana Windarto Agus Wantoro Agustina, Intan Ahdan, Syaiful 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 Ari Sulistiyawati Ariany, Fenty Arie Qur’ania Arief Budiman Arshad, Muhammad Waqas Arsi Hajizah Asistyasari, Ayuni Ayu Megawaty, Dyah Bustanul Ulum Chandra, Iryanto Damayanti Damayanti Damayanti, Damayanti Daniarti, Yeni Daniel Prasetyo Tarigan Deas Andrian Dwijaya Debby Alita Dedi Darwis Dedi Triyanto Desyanti Dinda Titian Lestari Dodi Siregar Dodi Siregar Dwi Satria, M. Najib Dyah Aminatun Dyah Ayu Megawaty Eko Bagus Fahrizqi Erlin Windia Ambarsari Fadila Shely Amalia Fajar Irvansyah Faruk Ulum Febrianus Gea Ferico Octaviansyah Pasaribu, Ahmad Fernando, Yusra Fikri Hamidy Gibtha Fitri Laxmi Hamdan Sobirin, Muhammad Heni Sulistiani Heni Sulistiani Ida Mayanju Pandiangan Imam Ahmad Imam Ahmad Isnain, Auliya Rahman Jeperson Hutahaean Jumaryadi, Yuwan 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 Merlin Puspita Sari Mesran Mesran Mesran, Mesran Mohammad Taufan Asri Zaen Muhaqiqin muhaqiqin Ni Komang Ratih Kumala Nirwana Hendrastuty Nuari, Reflan Nuralia Nuralia Nurman Fadhlullah nurnaningsih, Desi Nuzuliarini Nuris Octaviansyah, A. Ferico Oprasto, Raditya Rimbawan Palupiningsih, Pritasari Parjito Parjito Pasaribu, A. Ferico Octaviansyah Pasha, Donaya Permata, Permata Pramuditya, Andri Prastowo, Kukuh Adi Priandika, Adhie Thyo 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 Rahmadianti, Fitrah Amalia Rahman, Miftahur Rasli, Roznim Mohamad Reflan Revife Purba Rilo Nur Devija Rini Nuraini Riska Aryanti Riska Aryanti Rohmat Indra Borman Romadhoni, Randi Roswita Daeli Roznim, Roznim Ruziana binti Mohamad Rasli Ryan Randy Suryono S. Samsugi Safi, Mudar Sanriomi Sintaro Saputra, Alvin Setiawan, Dandi Setyani, Tria Sinta, Ratna Sari Roma Siti Mahmuda Sitna Hajar Hadad Sofiansyah Fadli Sri Agustiani Br Siburian Subhan Subhan Sufiatul Maryana Sufiatul Maryana Sumanto, Sumanto Surahman, Ade Susanto, Erliyan Redy Sussolaikah, Kelik Syaiful Ahdan Temi Ardiansah Trisnawati, Fika Ulum, Faruk Untoro Adji Very Hendra Saputra Very Hendra Saputra Wahyudi, Agung Deni Wang, Junhai Waqas Arshad, Muhammad Widiyanti, Adella yasin, ikbal Yohanes Eka Wibawa Yuliani, Asri Yuri Rahmanto Yusra Fernando