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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) 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
Setiawansyah Setiawansyah
(Scopus ID : 57446859700), Universitas Teknokrat Indonesia
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Combination of EDAS Method and Entropy Weighting in the Selection of the Best Customer Service Setiawansyah Setiawansyah
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 2 No. 3 (2024): Volume 2 Number 3 July 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v2i3.144

Abstract

Customer service is an integral part of a business that is responsible for providing service, support, and solutions to customers before, during, and after the purchase process. Selecting the best Customer Service is an important process in supporting a company's success in providing an exceptional customer experience. The main problems in assessing the best customer service are often related to subjectivity and gaps in data collection and analysis. Less clear or unstandardized assessment criteria can lead to bias, especially if the evaluation relies on the opinion of a particular individual without any supporting quantitative data. The purpose of this study is to apply the combination of EDAS method with Entropy Weighting in the selection process of the best customer service to produce an objective, transparent, and efficient scoring system by combining Entropy's ability to automatically determine the weight of criteria based on existing data, and using EDAS to evaluate and rank alternatives based on their distance from the average solution. Based on the ranking results in the best customer service alternative ranking, Andi occupies the first position with the highest score, which is 0.6017. In second place is Rina with a score of 0.5728, followed by Budi in third place with a score of 0.5053. Farhan is in fourth place with a score of 0.5. Furthermore, Siti took fifth place with a score of 0.4448, followed by Laila in sixth place with a score of 0.4172. Dewi is in seventh position with a score of 0.352, while Ahmad is in last position with the lowest score, which is 0.0928.
Integrating Method based on the Removal Effects of Criteria in Multi-Attribute Utility Theory for Employee Admissions Decision Making Setiawansyah Setiawansyah
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 2 No. 4 (2024): Volume 2 Number 4 October 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v2i4.151

Abstract

Effective employee onboarding is essential for the success of an organization because it can ensure that the company acquires quality human resources that are in line with the needs and culture of the company. Careful employee recruitment based on objective evaluation is key in creating a competent team and supporting the achievement of the company's goals. Problems in employee recruitment often arise due to a lack of an objective and transparent selection process, which can lead to improper selection of candidates. One of the main challenges is the presence of errors in judgment, which reduces the diversity and quality of the team formed. The purpose of the study is to combine the principles of multi-attribute utility theory (MAUT) with method based on the removal effects of criteria (MEREC) to improve the decision-making process in employee recruitment which can improve objectivity, accuracy, and efficiency in the recruitment process, as well as reduce possible errors in the assessment of candidates. The results of the employee acceptance ranking using a combination of MEREC and MAUT were obtained by Clara Wijaya occupying the first position with the highest score of 0.7606, followed by Farah Ramadhani with a score of 0.7525. The third position was filled by Andi Santoso with a score of 0.4874. These ratings provide an overview of each individual's performance or eligibility based on a specific assessment.
Multi-Criteria Approach in Selecting Optimal Retail Store Locations Using Integration of LODECI and ERVD Methods Setiawansyah Setiawansyah; Ajeng Savitri Puspaningrum
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 4 No. 2 (2026): Volume 4 Number 2 April 2026
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v4i2.250

Abstract

Selecting an optimal retail store location is a complex multi-criteria decision-making problem involving conflicting factors such as cost, accessibility, demographics, competition, and market potential. This study proposes an integrated approach combining the LODECI (Logarithmic Decomposition of Criteria Importance) method and the ERVD (Election based on Relative Value Distances) method to improve the objectivity, accuracy, and stability of decision results. LODECI is applied to determine criterion weights based on data distribution characteristics using logarithmic decomposition, reducing subjectivity in the weighting process. Subsequently, ERVD is utilized to evaluate and rank alternatives based on their relative distances to ideal and non-ideal solutions, enabling a more comprehensive assessment of each location. The research results show that the proposed integration effectively produces consistent and discriminative rankings, with Location F having a value of 0.9759 identified as the best alternative, followed by Location E with a value of 0.8461 and Location C with a value of 0.7882. Overall, the integration of LODECI and ERVD provides a robust decision-making framework that enhances reliability in selecting optimal retail store locations in complex and heterogeneous environments.
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): JEECS (Journal of Electrical Engineering and Computer Sciences) - In press
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.
A Pythagorean Fuzzy-Based MUNRA Method for Handling Uncertainty in Complex Decision Environments Setiawansyah Setiawansyah
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 4 No. 2 (2026): Volume 4 Number 2 June 2026
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v4i2.273

Abstract

This research develops the Pythagorean Fuzzy Multi-Normalized Rating Analysis (PF-MUNRA) method as a novel approach to address uncertainty and ambiguity in multi-criteria decision making. The main contribution of this study lies in the integration of Pythagorean Fuzzy Sets with a multi-normalization framework consisting of linear, vector, and non-linear normalization within a single decision-making model, enabling more flexible, comprehensive, and unbiased evaluation results compared to conventional single-normalization approaches. This method integrates the concept of Pythagorean Fuzzy Sets, which can represent degrees of membership and non-membership more flexibly, with the multi-normalization approach in MUNRA. Unlike previous studies that generally apply fuzzy environments and normalization techniques separately, the proposed PF-MUNRA simultaneously combines fuzzy uncertainty handling, multi-normalization mechanisms, and objective weighting to improve ranking consistency and decision robustness. In addition, weighted aggregation is used to produce more accurate preference values and reflect the relative importance of each criterion. The experimental results demonstrate that PF-MUNRA produces stable alternative rankings with Spearman correlation values ranging from 0.9464 to 1.0000 under various weight-change scenarios, indicating a very strong level of ranking consistency and robustness. Comparative analysis shows changes in alternative positions that reflect the capability of the proposed method to capture data complexity more effectively than the initial approach, while sensitivity analysis confirms that variations in criterion weights do not significantly affect the final ranking results, thereby proving that PF-MUNRA has high stability and reliability in dynamic and uncertain decision-making environments.
REFORMULATION OF MULTI-ATTRIBUTE UTILITY THEORY NORMALIZATION TO HANDLE ASYMMETRIC DATA IN MADM Ajeng Savitri Puspaningrum; Erliyan Redy Susanto; Nirwana Hendrastuty; 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
Integration of CRISUS Weighting and ROV Method for Division Head Performance Evaluation in a Manufacturing Company Junhai Wang; Setiawansyah Setiawansyah; Pritasari Palupiningsih
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 7 No. 1 (2026): Mei 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/reputasi.v7i1.12511

Abstract

The performance evaluation of division heads in manufacturing companies often faces various problems, such as high subjectivity in assessment, the absence of clear criteria weighting standards, and instability in ranking results due to data variation. This situation causes the evaluation results to be less consistent and less able to accurately represent performance. Therefore, this study aims to develop a more objective performance evaluation model by integrating the CRISUS and ROV methods. The CRISUS method is used to determine the criteria weights objectively based on the characteristics of data distribution, while the ROV method is used to rank alternatives by considering variations in performance values through upper and lower bound approaches. The criteria used include leadership, productivity, innovation, operational costs, and error rates. The research results indicate that the proposed model is able to produce more stable and consistent preference values in representing candidate performance. Based on the calculation results, CDT-03 obtained a preference value of 0.4316 and ranked first, followed by CDT-06 with a value of 0.4212 in second place, and CDT-01 in third place with a value of 0.3180. Meanwhile, CDT-02 was in the last position with a value of 0.0739. These findings show that the integration of the CRISUS and ROV methods is able to provide a more objective, comprehensive, and reliable evaluation in supporting managerial decision-making. This research provides several important contributions; this combination is able to overcome the weaknesses of conventional methods by presenting objective criteria weighting as well as a ranking mechanism that takes into account variations in performance conditions.
Comparison of Objective Weighting Methods in SAW and Their Effect on Alternative Ranking Results Junhai Wang; Setiawansyah Setiawansyah; Sumanto Sumanto
Jurnal Masyarakat Informatika Vol 17, No 1 (2026): May 2026
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.
Employee Performance Evaluation Using RECA-based Weighting and RAWEC: Evidence from Textile Manufacturing Setiawansyah Setiawansyah; Junhai Wang; Sufiatul Maryana; Pritasari Palupiningsih
Jurnal Buana Informatika Vol. 17 No. 1 (2026): Jurnal Buana Informatika, Volume 17, Nomor 1, April 2026
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v17i1.13709

Abstract

Employee performance evaluation in the textile industry production division still faces issues of subjectivity, limited indicators, and inconsistency in ranking that do not yet reflect the real contribution of employees. This study aims to assess employee performance using a multi-criteria decision-making approach by integrating the RECA method for determining objective criterion weights and the RAWEC method for generating performance rankings. Performance data is collected based on several key criteria, namely work productivity, production quality, timeliness, work discipline, and production error rates, which reflect the operational conditions in the textile manufacturing environment. The analysis results indicate that the applied approach clearly distinguishes employee performance and produces a stable ranking, with Gina taking first place with a final score of 0.483 and Citra with a score of 0.2933. These findings indicate that RECA and RAWEC support more reliable and data-driven managerial decisions in the textile industry.   Evaluasi kinerja karyawan di divisi produksi industri tekstil masih menghadapi masalah subjektivitas, keterbatasan indikator, dan ketidakkonsistenan pemeringkatan yang belum mencerminkan kontribusi nyata karyawan. Penelitian ini bertujuan untuk menilai kinerja karyawan menggunakan pendekatan pengambilan keputusan multi-kriteria dengan mengintegrasikan metode RECA untuk menentukan bobot kriteria objektif dan metode RAWEC untuk menghasilkan peringkat kinerja. Data kinerja dikumpulkan berdasarkan beberapa kriteria utama, yaitu produktivitas kerja, kualitas produksi, ketepatan waktu, disiplin kerja, dan tingkat kesalahan produksi, yang mencerminkan kondisi operasional pada lingkungan manufaktur tekstil. Hasil analisis menunjukkan bahwa pendekatan yang diterapkan mampu membedakan kinerja karyawan secara jelas dan menghasilkan pemeringkatan yang stabil, di mana Gina menempati peringkat pertama dengan nilai akhir 0.483 Citra dengan nilai 0,2933. Temuan ini menunjukkan RECA dan RAWEC mendukung keputusan manajerial yang lebih andal dan berbasis data di industri tekstil.
Objective Approach in Supplier Selection: Integration of RECA Weighting and Combinative Distance-based Assessment Method Setiawansyah Setiawansyah; Iryanto Chandra
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 4 No. 3 (2026): Volume 4 Number 3 July 2026
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v4i3.264

Abstract

Supplier selection is a strategic decision that directly affects operational efficiency and supply chain performance. This study aims to propose a multi-criteria decision-making approach to evaluate and rank suppliers objectively based on multiple performance indicators. The evaluation is conducted using five main criteria, namely price, quality, delivery, responsiveness, and capacity and flexibility. A total of nine supplier alternatives were assessed, and a quantitative decision model was applied to aggregate the performance of each alternative into a final score and ranking. The results indicate that the proposed approach is capable of clearly distinguishing supplier performance, as reflected in the significant differences in final scores across alternatives. The ranking results show that PT Cipta Solusi Persada achieved the first position with a final score of 0.5171, followed by PT Karya Nusantara with a score of 0.4626 in the second position, and PT Prima Logistik Indonesia with a score of 0.3922 in the third position. These findings demonstrate that suppliers with balanced performance across all criteria tend to achieve higher rankings. The study also highlights that suppliers with lower rankings generally exhibit structural weaknesses in key criteria, suggesting the need for performance improvement or strategic reconsideration.
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 Ariany, Fenty Arie Qur’ania Arief Budiman 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 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 Fajar Irvansyah Faruk Ulum Faruk Ulum Febrianus Gea Fernando, Yusra Fikri Hamidy Gibtha Fitri Laxmi Hamdan Sobirin, Muhammad Heni Sulistiani Heni Sulistiani Ida Mayanju Pandiangan Imam Ahmad Imam Ahmad Iryanto Chandra Isnain, Auliya Rahman Jeperson Hutahaean Jumaryadi, Yuwan 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 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 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 Rilo Nur Devija Rini Nuraini 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 Sufiatul Maryana Sumanto Sumanto Sumanto 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 Very Hendra Saputra Wahyudi, Agung Deni Wang, Junhai Waqas Arshad, Muhammad Widiyanti, Adella yasin, ikbal Yohanes Eka Wibawa Yuliani, Asri Yuri Rahmanto Yusra Fernando