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All Journal Bulletin of Electrical Engineering and Informatics 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 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) 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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IT Personnel Recruitment Decision Support System: Combination of TOPSIS and Entropy Weighting Methods Setiawansyah, Setiawansyah
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 2 No. 3 (2024): Volume 2 Number 3 September 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v2i3.131

Abstract

IT personnel recruitment is an important process that aims to get the best talent in the field of information technology to support operations and innovation in an organization. IT personnel recruitment faces several key challenges that often make it difficult for companies to find the right candidates. One of the main problems is that the recruitment process can also be constrained by difficulties in assessing a candidate's cultural and interpersonal fit, where high technical skills are not necessarily balanced by good communication and teamwork skills. The purpose of this study is to apply DSS that integrates the TOPSIS and entropy weighting methods in the IT recruitment process, so that it can help companies select the best candidates effectively and objectively. The system is designed to improve the accuracy of candidate identification through multi-criteria analysis. An IT personnel recruitment decision support system that combines TOPSIS and entropy methods is an innovative approach designed to increase effectiveness in selecting the best candidates based on relevant criteria. The results of Candidate G ranking were ranked highest with a score of 0.932, followed by Candidate A with a score of 0.7069, Candidate C with a score of 0.645, and Candidate E with a score of 0.6443. Furthermore, Candidate I in the middle position with a score of 0.5023, followed by Candidate D with a score of 0.3417. Candidate B and Candidate H are in a lower position with values of 0.2188 and 0.1817, respectively. Candidate F ranked at the bottom with a score of 0.0519.
Integration of Root Assessment Method and Entropy Weighting in Determining Business Location Selection Setiawansyah, Setiawansyah
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 2 No. 4 (2024): Volume 2 Number 4 December 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v2i4.141

Abstract

Business location is one of the key factors in determining the success of a business. Choosing the right location can affect customer accessibility, operational costs, and a company's competitiveness in the market. Determining the location of a business is often faced with various problems that can affect the success and continuity of the business. One of the main challenges is the accessibility and reach of the market, and un-strategic or hard-to-reach locations can limit customer potential and reduce business appeal. Another problem is that it often arises from the diversity of criteria that must be taken into account and the importance of each criterion varies depending on the type of business. The purpose of this study is to apply a more objective approach in determining business locations by integrating the root assessment method and entropy weighting methods in systematically evaluating various business location criteria and giving fair weight based on their level of importance. By applying this combination of methods, the decision-making process becomes more accurate and in accordance with business needs, and provides solutions that can be adapted by various types of businesses in determining strategic locations that support long-term success. Business location ranking shows the highest rated location is Location 6, with a score of 4.4254. Furthermore, Location 10 is ranked second with a score of 4.3993, followed by Location 2 in third place with a score of 4.3916. These results show that Location 6 is the most superior location in this assessment.
G2M weighting: a new approach based on multi-objective assessment data (case study of MOORA method in determining supplier performance evaluation) Hendrastuty, Nirwana; Setiawansyah, Setiawansyah; An’ars, M. Ghufroni; Rahmadianti, Fitrah Amalia; Saputra, Very Hendra; Rahman, Miftahur
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp403-416

Abstract

Criteria weighting methods in decision support system (DSS) face various challenges and limitations that can affect their accuracy and reliability. One of the main challenges is subjectivity, this subjective assessment can reduce the objectivity and consistency of results. The main objective of the new weighting method grey geometric mean (G2M) weighting is to provide more objective and robust criteria weights under conditions of uncertainty and incomplete data. The new G2M weighting approach has a significant potential impact on the DSS field, it has the potential to generate more effective and efficient decisions, which can improve organizational performance, reduce risk and optimize outcomes. Pearson correlation test results of two sets of rankings generated by DSS methods namely grey relational analysis (GRA), simple additive weighting (SAW), multi-attributive ideal-real comparative analysis (MAIRCA), weighted product (WP), combined compromise solution (COCOSO), vlsekriterijumska optimizacija i kompromisno resenje (VIKOR), and a new additive ratio assessment (ARAS) that there is a strong positive correlation between the two methods using G2M weighting criteria. The high correlation value indicates that the rankings of the methods used tend to move together, giving confidence in the consistency and validity of the resulting ranking results. This gives confidence that both methods can be used simultaneously or interchangeably with consistent results. The use of G2M weighting in the DSS method used can support better decision-making by providing consistent information and validity of ranking results.
Development of a Decision Support System Based on New Approach Respond to Criteria Weighting Method and Grey Relational Analysis: Case Study of Employee Recruitment Selection Megawaty, Dyah Ayu; Damayanti, Damayanti; Sumanto, Sumanto; Permata, Permata; Setiawan, Dandi; Setiawansyah, Setiawansyah
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2744

Abstract

The purpose of this research is to propose a new approach in the criteria weighting method using the RECA method, the RECA method can help provide a systematic and structured framework for determining criteria weights in multi-criteria decision making. The determination of weights using the RECA method is to increase objectivity and accuracy in the candidate assessment and selection process by determining the appropriate weight for each criterion based on responses and assessments from experts or stakeholders. Testing the RECA Method with Multi Attribute Decision Making (MADM) techniques is an important step in measuring the effectiveness of the RECA Method in the context of multi-criteria decision making. Ranking tests using Spearman correlation between the RECA method and other methods such as SAW with a correlation value of 1, MOORA with a correlation value of 0.9636, MAUT with a correlation value of 0.9515, WP with a correlation value of 0.891, SMART with a correlation value of 0.9636, and TOPSIS with a correlation value of 0.8788 show a high level of rank consistency between the RECA method and these methods. This indicates that the RECA Method has a strong ability to generate similar candidate rankings with other methods, validating its reliability and consistency in the context of multi-criteria decision making. Implications for further research include exploring the application of the RECA method in different decision-making contexts other than recruitment, such as performance evaluation, project selection, or supplier selection. Further research could investigate the integration of the RECA method with other decision-making methods or algorithms to improve its performance and applicability in complex decision environments. Comparative studies with larger sample sizes and diverse datasets can provide deeper insights into the effectiveness and reliability of the RECA method compared to other methods.
DYNAMIC WEIGHT ALLOCATION IN MODIFIED MULTI-ATRIBUTIVE IDEAL-REAL COMPARATIVE ANALYSIS WITH SYMMETRY POINT FOR REAL-TIME DECISION SUPPORT Hadad, Sitna Hajar; Chandra, Iryanto; Wang, Junhai; Megawaty, Dyah Ayu; Setiawansyah, Setiawansyah; Yudhistira, Aditia
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4170

Abstract

Decision Support Systems (DSS) have a crucial role in real-time decision-making, especially in the digital era that demands high speed and accuracy. Managing criterion weights in a dynamic environment presents significant challenges due to rapid and unpredictable changes in conditions. However, determining an accurate weight becomes difficult due to uncertainty, incomplete data, and subjective factors from decision-makers. In addition, changes in the external environment, such as market trends, regulations, or customer preferences, can affect the relevance of each criterion, thus requiring a real-time weight adjustment mechanism. The purpose of this study is to develop and explore the dynamic weight allocation method in symmetry point- multi-attributive ideal-real comparative analysis (S-MAIRCA) to support more accurate and responsive real-time decision-making in a dynamic environment. This research contributes to the understanding of how the weights of criteria can be adjusted automatically and responsively to changing conditions or new data, which increases the relevance and accuracy of decisions in a dynamic environment. The urgency of S-MAIRCA research is important because it often involves real-time, dynamic, and complex data. This development not only improves the adaptability of the S-MAIRCA method, but also contributes significantly to creating computer science-based applications that are more intelligent, flexible, and relevant to the evolving needs of the system. The results of the alternative ranking comparison using the CRITIC-MAIRCA, LOPCOW-MAIRCA, ROC-MAIRCA, and S-MAIRCA methods showed variations in the ranking order generated for each alternative using spearman correlation. The results of the correlation value of CRITIC-MAIRCA and LOPCOW-MAIRCA have a very high correlation of 0.993, which shows that these two methods provide almost identical rankings in alternative evaluation. Likewise, CRITIC-MAIRCA and S-MAIRCA had a high correlation of 0.979, signaling a strong similarity in ranking results despite slight differences in the approaches used by the two methods. The results of the application of the MAIRCA-S method in the development of DSS based on real-time data have a significant impact on improving the speed, accuracy, and adaptability of decisions. MAIRCA-S strengthens the validity of decision results by considering a variety of attributes on a more comprehensive scale, providing added value in the development of DSS for various industrial sectors.
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
Co-Authors Abhishek R Mehta Ade Dwi Putra Ade Surahman Adhie Thyo Priandika 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 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 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 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 Syaiful Ahdan Trisnawati, Fika Ulum, Faruk Untoro Adji Very Hendra Saputra Very Hendra Saputra Wahyudi, Agung Deni Wang, Junhai Waqas Arshad, Muhammad Wibawa, Yohanes Eka Widiyanti, Adella yasin, ikbal Yuliani, Asri Yuri Rahmanto