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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
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Penerapan Metode SWARA dan Grey Relational Analysis Dalam Pemilihan Karyawan Terbaik Very Hendra Saputra; Setiawansyah Setiawansyah
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 2 No. 1 (2024): Volume 2 Number 1 March 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v2i1.107

Abstract

The best employees are individuals who not only have exceptional expertise in their work, but also stand out in their attitude, dedication, and engagement towards the job and the company. One of the problems that often arises in the selection of the best employees is the lack of congruence between the skills possessed and the lack of transparency and communication in the best employee appraisal process to understand what is expected by the company. This study aims to select the best employees by applying a combination of the SWARA method for determining the weight of criteria and the GRA method for selecting the best employees based on the data from the assessment results that have been carried out. The final score ranking results recommend for the best employee 1 with a final score of 0.1799 on behalf of Desi Puspasari, the best employee 2 with a final value of 0.1147 on behalf of M. Budianto, and the best employee 3 with a final score of 0.1082 on behalf of Akhmadi.
Penerapan Metode Logarithmic Percentage Change-Driven Objective Weighting dan Multi-Attribute Utility Theory dalam Penerimaan Guru Bahasa Inggris Setiawansyah Setiawansyah; Ari Sulistiyawati
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 2 No. 2 (2024): Volume 2 Number 2 June 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v2i2.119

Abstract

The admission of English teachers in private schools is an important process in ensuring the quality of education in the institution. This process involves several stages, from the announcement of job vacancies to the selection of candidates who match the established criteria. Problems in the recruitment of English teachers, namely a selection process that lacks transparency or inadequate evaluation tools, can also be an obstacle. Therefore, addressing the problem of English teacher recruitment requires a holistic approach that pays attention to various aspects, including the development of effective recruitment strategies, the provision of training to improve candidate qualifications, and the improvement of the overall selection process. The research objective of applying the LOPCOW (Logarithmic Percentage Change-Driven Objective) Weighting and MAUT (Multi-Attribute Utility Theory) method is to provide a comprehensive and effective framework in the selection process, where LOPCOW is used to analyze objective data related to teacher performance and qualifications, while MAUT is used to integrate the subjective preferences of stakeholders such as principals and school committees in decision making. Thus, the main objective is to optimize the admission process of English teachers by considering these two aspects holistically. The ranking results show that the final results of English teacher admissions recommend the first rank with a final score of 0.7421 obtained by HR Teacher Candidates. This result is the application of the LOPCOW and MAUT methods in the selection process for English teacher admission, and becomes a recommendation for the English teacher admission process.
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.
Evaluation of Recruitment Candidates Based on Data Objectivity Using LOGSTA and CORASO Integration Setiawansyah Setiawansyah
Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi Vol. 12 No. 1 (2026): April 2026
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jtk3ti.v12i1.19575

Abstract

The employee selection process often faces problems such as evaluator subjectivity, inconsistency between criteria, and decision biases, which affect the stability of candidate ranking results. This study aims to develop a decision support system for recruitment candidate evaluation that emphasizes data objectivity and consistency in assessment results. The proposed approach integrates the LOGSTA method as an objective-criteria weighting technique based on logarithmic transformation and CORASO as an alternative ranking method based on ideal–compromise solutions. LOGSTA is used to determine criteria weights objectively based on data dispersion and information content, while CORASO is utilized to comprehensively evaluate and rank candidates. The research results show that the proposed method is capable of producing a stable and transparent ranking of candidates, as well as reducing subjective bias in the selection process. Based on the final CORASO scores, candidate Gina ranked first with a score of 0.5055, followed by Nugroho in second place with a score of 0.4039, and Saputra in third place with a score of 0.3024. Scenario analysis of changes in criteria weights also indicates that the rankings of the top candidates are relatively consistent, reaffirming the reliability of the proposed approach in supporting fair and data-driven recruitment decision-making.
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.
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