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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) 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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Optimizing Employee Admission Selection Using G2M Weighting and MOORA Method Rahmanto, Yuri; Wang, Junhai; Setiawansyah, Setiawansyah; Yudhistira, Aditia; Darwis, Dedi; Suryono, Ryan Randy
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.
Multi-Criteria Decision Support System for Best Warehouse Performance Selection Using Combined Compromise Solution Method Wang, Junhai; Setiawansyah, Setiawansyah; Isnain, Auliya Rahman
Bulletin of Data Science Vol 4 No 2 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletinds.v4i2.7196

Abstract

Selecting the best performing warehouse is a strategic step in supporting the efficiency of the supply chain and distribution of goods. This research aims to design a multi-criterion-based decision support system in evaluating and determining the best warehouse using the Combined Compromise Solution (CoCoSo) method. This method was chosen for its ability to combine the strength of weighted average approaches and relative compromises between alternatives, resulting in more balanced and objective decisions. This research involves eight warehouse alternatives that are assessed based on a number of relevant performance criteria. The process starts from problem identification, determination of criteria, data collection, normalization, weighting, to the application of the CoCoSo method. The final results showed that Warehouse C obtained the highest score of 4.8155, followed by Warehouse E and Warehouse A, indicating that the three warehouses had the best performance. These findings are expected to be a reference in strategic decision-making related to warehousing management as well as the basis for the development of a data-based performance evaluation system.
Combination of MEREC and WASPAS Methods for Performance Assessment in the Decision Support System for Member Admission for the Metaverse Team Putra, Ade Dwi; Rahmanto, Yuri; Darwis, Dedi; Aldino, Ahmad Ari; Setiawansyah, Setiawansyah
Bulletin of Informatics and Data Science Vol 3, No 1 (2024): May 2024
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v3i1.100

Abstract

The selection of the right team members is critical to the success of complex and multidisciplinary Metaverse projects, the previous method used in this selection employed criteria weights based on individual evaluator assessments.. This study proposes the application of a combination of MEREC (method based on the removal effects of criteria) and WASPAS (weighted aggregated sum product assessment) methods to build a DSS in the selection of Metaverse team members. The MEREC method is used to determine the weight of relevant criteria, such as technical skills, communication, innovation, problem-solving, team collaboration, and experience. Meanwhile, the WASPAS method is used to rank candidates based on evaluation scores calculated using a combination of the Weighted Sum Model (WSM) and the Weighted Product Model (WPM). The results showed that the candidate with the highest score was Member Candidate 5 with a score of 0.9806, followed by Member Candidate 11 with a score of 0.944 and Member Candidate 9 with a score of 0.9433. This research proves that the combination of MEREC and WASPAS methods can be used effectively to select team members who have the best quality and are in accordance with the needs of Metaverse projects. A major contribution of this research is the development of a more objective and structured method for the selection of team members in technology projects that require multidisciplinary expertise
Selection of the Best E-Commerce Platform Based on User Ratings using a Combination Entropy and SAW Methods Ulum, Faruk; Wang, Junhai; Setiawansyah, Setiawansyah; Aryanti, Riska
Bulletin of Informatics and Data Science Vol 3, No 2 (2024): November 2024
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v3i2.92

Abstract

Choosing the right e-commerce platform has a crucial role for consumers and business actors. For consumers, a reliable and user-friendly platform provides a safe, convenient, and efficient shopping experience. Considering various aspects of choosing the right e-commerce platform is a strategic investment that can provide long-term added value for all parties involved in the digital ecosystem. The purpose of this study is to identify and determine the best e-commerce platforms based on user experience and assessment with an objective and structured decision-making approach using a combination of Entropy and SAW methods. The results of the ranking of the best e-commerce platform selection determined through the combination of the Entropy and SAW methods, obtained that Shopee ranked first with the highest preference value of 0.9819, followed by Tokopedia in second place with a value of 0.973. Furthermore, Blibli is in third place with a score of 0.9401, followed by Lazada with a score of 0.9305, and the last is Bukalapak with a score of 0.9021. This research makes a significant contribution to multi-criteria decision-making by applying a combination of Entropy and SAW methods to evaluate and determine the best e-commerce platform based on user assessments. The results of this research can be used as a practical reference as a basis for strategic decision-making in choosing the e-commerce platform that best suits market needs
Selection of the Best Customer using a Combination of Rank Order Centroid and Grey Relational Analysis Arshad, Muhammad Waqas; Rahmanto, Yuri; Setiawansyah, Setiawansyah
Bulletin of Informatics and Data Science Vol 3, No 1 (2024): May 2024
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v3i1.84

Abstract

A customer is an individual or entity that purchases goods or services from a company or organization. They play an important role in business success, as customer satisfaction and loyalty can determine a company's reputation and sustainability in the marketplace. One of the main challenges is collecting and analyzing accurate and comprehensive data regarding purchase behavior, transaction frequency. Other challenges include keeping customer data confidential and ensuring that the selection process is fair and transparent. The ROC method is used in the initial stage to determine the importance weight of each criterion based on the subjective ranking of the decision makers, which is then converted into numerical weights systematically and consistently, the GRA method is applied to calculate the relational proximity between each customer's alternative to the ideal solution based on their performance values on each criterion.The purpose of this study is to develop and implement a comprehensive framework for the selection of the best customers by combining ROC weighting and GRA methods, and provide practical recommendations for companies in managing and utilizing the best customer relationships, in order to improve customer loyalty and long-term profitability. By combining these approaches, businesses can effectively prioritize customers based on their significance and potential to build long-term relationships and maximize profitability, thus enabling more targeted marketing strategies and better resource allocation. The best customer ranking results were obtained by Customer I with a final GRG value of 0.1792 for the 1st rank, Customer D with a final GRG value of 0.1683 for the 2nd rank, and Customer K with a final GRG value of 0.1505 for the 3rd rank
Hybrid G2M Weighting and WASPAS Method for Business Partner Selection: A Decision Support Approach Wang, Junhai; Setiawansyah, Setiawansyah; Alita, Debby
Journal of Computer System and Informatics (JoSYC) Vol 6 No 3 (2025): May 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i3.7229

Abstract

Choosing the right business partner is a crucial factor in the success and continuity of a company's operations. The main issue in selecting business partners is the complexity of balancing various interconnected and often conflicting factors. Another problem lies in the subjectivity and limitations of information. Evaluators or decision-makers may have differing views on the priority of criteria or the interpretation of the available data. This study proposes a hybrid method-based decision support system approach that combines G2M Weighting and WASPAS to address the challenges in complex and uncertain multi-criteria evaluations. The G2M method is used to objectively determine the weight of criteria based on geometric averages in gray environments, so as to be able to capture data variability and uncertainty. Furthermore, the WASPAS method is applied to calculate the final value and rank the alternative business partners based on a combination of additive and multiplicative approaches. The ranking chart for business partner selection using the G2M Weighting and WASPAS method shows that Partner G gets the highest score of 9.93E+03, followed by Partner A and Partner E who have the same score of 9.43E+03. Meanwhile, Partner D had the lowest score, which was 5.97E+03. This ranking of business partner selection shows that Partner G is the best choice as a business partner based on the evaluation method used. The results of the study show that this hybrid approach provides more accurate, stable, and comprehensive evaluation results than conventional methods. This approach can be an effective solution for companies in supporting the strategic decision-making process in choosing the best business partners.
An Entropy-Assisted COBRA Framework to Support Complex Bounded Rationality in Employee Recruitment Oprasto, Raditya Rimbawan; Wang, Junhai; Pasaribu, A Ferico Octaviansyah; Setiawansyah, Setiawansyah; Aryanti, Riska; 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.
Penerapan Metode Additive Ratio Assement (ARAS) dalam Pemilihan Customer Service Terbaik Sri Agustiani Br Siburian; Mohammad Taufan Asri Zaen; Setiawansyah; Dodi Siregar; Erlin Windia Ambarsari; Yuwan Jumaryadi
Journal of Informatics Management and Information Technology Vol. 3 No. 1 (2023): January 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v3i1.239

Abstract

There are several references or assessments in determining the best customer service, including those based on customer service performance assessments, namely Cross Selling, Greeting Service Recovery, Grooming, and Discipline. In this study the authors used the ARAS method in selecting the best Customer Service. Use the Additive Ratio Assessment (ARAS) method where each criterion is compared to produce the best. The results of the study provide alternative A3 which is the alternative chosen to be the best alternative with a value of 0.2207.
Sistem Pendukung Keputusan Rekomendasi Pengangkatan Karyawan Kontrak Menjadi Karyawan Tetap Menerapkan Metode Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) Laurent Nababan; Roswita Daeli; Dodi Siregar; Erlin Windia Ambarsari; Setiawansyah; Sofiansyah Fadli
Journal of Informatics Management and Information Technology Vol. 3 No. 2 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v3i2.254

Abstract

PT. Indoramah Abadi is a national plastic manufacturing company that focuses on the production of mineral water packaging. Because the amount of goods produced is quite large, the company has a large number of employees, including contract employees and permanent employees. However, the large number of employees can cause problems in determining which contract employees will be appointed as permanent employees. This problem occurs because the company does not have objective criteria in selecting permanent employees, causing jealousy among employees. In addition, the calculation process used is still manual and inaccurate, thus affecting employee performance. To overcome these problems, the authors conducted research using the MOORA method. This method is a method that can assist in making decisions by using complex mathematical calculations that can be used to solve problems in conflicting criteria, namely benefits and costs. The results of the study show that alternative A4 with a value of 0.2106 is the highest score. Therefore, it can be concluded that a contract employee named Aksa Alpindo deserves to be appointed as a permanent employee.
RAM-MEREC (Root Assessment Method - Method based on Removal Effects of Criteria): A Synergistic Approach to Weight Derivationand Alternative Ranking in the Selection of the Best Intern Employees Permata, Permata; Wang, Junhai; Setiawansyah, Setiawansyah; Pasaribu, A. Ferico Octaviansyah; Wahyudi, Agung Deni
TIN: Terapan Informatika Nusantara Vol 5 No 11 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i11.7198

Abstract

An effective intern selection process requires an objective and systematic approach to decision-making, especially when it involves multiple assessment criteria. This study proposes a combined approach of RAM-MEREC, which is a combination of Method based on Removal Effects of Criteria (MEREC) and Root Assessment Method (RAM), as a method to improve accuracy and reliability in the best internal selection. MEREC is used to objectively determine the weight of criteria based on the impact of the elimination of each criterion on the overall outcome. Meanwhile, RAM is used to generate alternative rankings by considering the root impact of value changes on each candidate's performance. The results of the application of this method show that RAM-MEREC is able to provide a more representative weighting and a more stable and consistent final ranking. The results of the application of this method show that RAM-MEREC is able to provide a more representative weighting and a more stable and consistent final ranking. The results of the calculation of the total score of all alternatives using the evaluation method that has been determined, obtained that Alternative 10 is the best candidate with the highest score of 1.4378, followed by Alternative 6 with a score of 1.4375 and Alternative 3 with a score of 1.4375. This approach not only improves the quality of decision-making, but also minimizes subjectivity and bias in the selection process.
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 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 Erliyan Redy Susanto 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 Iryanto Chandra Isnain, Auliya Rahman Jeperson Hutahaean Jumaryadi, Yuwan 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 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 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 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