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All Journal Format : Jurnal Imiah Teknik Informatika Computatio : Journal of Computer Science and Information Systems Jurnal CoreIT Building of Informatics, Technology and Science Indonesian Journal of Electrical Engineering and Computer Science Journal Social Science And Technology For Community Service Journal of Engineering and Information Technology for Community Service Journal of Computing and Informatics Research Bulletin of Informatics and Data Science Jurnal Media Borneo Jurnal Informatika dan Rekayasa Perangkat Lunak
Very Hendra Saputra
Prodi Magister Pendidikan Matematika, Pascasarjana, FKIP – UNS
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Decision Support System for Video Editing Staff Recruitment Using a Combination of Entropy and Simple Additive Weighting Methods Wang, Junhai; Saputra, Very Hendra; Putra, Ade Dwi; Anars, M. Ghufroni; Pasaribu, A. Ferico Octaviansyah; Ardiansah, Temi
FORMAT Vol 15, No 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2026.v15.i1.006

Abstract

The recruitment process for video editing staff is a strategic stage in ensuring the quality of professional and competitive content production. However, candidate assessment often faces challenges of subjectivity and inaccuracy in decision-making when evaluators rely solely on intuitive judgment without a measured approach. This study aims to develop a decision support system based on Multi-Criteria Decision Making (MCDM) by integrating the Entropy method for objective determination of criteria weights and the Simple Additive Weighting (SAW) method in calculating the preference values of alternatives. Five evaluation criteria are used in the selection process, namely Editing, Creativity, Experience, Discipline, and Teamwork, with the final weights obtained through the Entropy method being 0.2867, 0.2248, 0.2573, 0.0685, and 0.1626. The study results show that the SAW method is capable of processing candidate evaluation scores comprehensively based on these weights, producing final scores that indicate the best candidates, namely Eko Firmansyah (0.986), Indra Mahendra (0.9699), and Candra Wijaya (0.9662) as the three candidates with the highest eligibility. This study demonstrates that the integration of the Entropy–SAW method is effective in creating a selection mechanism that is objective, transparent, and scientifically accountable, thus making a significant contribution to decision-making in the field of human resource management
Hybrid Entropy and CRADIS Method Approach in Decision Support System for Selecting the Best Employees Wang, Junhai; Setiawansyah, Setiawansyah; Saputra, Very Hendra
Building of Informatics, Technology and Science (BITS) Vol 7 No 4 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i4.8985

Abstract

Selecting the right employees is a key factor in improving organizational performance and productivity. However, in many organizations, the employee selection process is still conducted through manual assessments and subjective judgments, which may lead to bias and inconsistent decisions. Therefore, a systematic and objective approach is needed to support the evaluation process. This study integrates the Entropy method and the CRADIS method within a decision support system to determine the best employee candidates. The Entropy method is applied to calculate objective criteria weights based on the variation of information in the data, while the CRADIS method is used to rank candidates according to their proximity to the ideal solution and distance from the anti-ideal solution. The integration of these two methods provides a framework that reduces subjectivity in determining criterion importance and produces more discriminative ranking results. The findings indicate that candidate GF achieved the highest score of 0.6848, followed by EY with 0.6835 and AR with 0.6528, showing that these candidates have performance profiles closest to the defined criteria. In addition, sensitivity analysis using several scenarios of criteria weight changes demonstrates that the proposed model is relatively stable, with an overall ranking consistency of 81.8%, while alternatives AR, DI, and FR show 100% ranking stability. These results indicate that the Entropy–CRADIS approach can improve the accuracy, objectivity, and reliability of employee selection decisions in multi-criteria decision-making environments.
Co-Authors Ahmad Ari Aldino Anars, M. Ghufroni An’ars, M. Ghufroni Ardiansah, Temi Arshad, Muhammad Waqas Asistyasari, Ayuni Chandra, Iryanto Dedi Darwis Febrianto, Endi Heni Sulistiani Ismail, Izudin Ismail, Izzudin Khoirunnisa, Yosi Mardiyana Mardiyana Nirwana Hendrastuty Pasaribu, A. Ferico Octaviansyah Priandika, Adhie Thyo Putra, Ade Dwi Rahmadianti, Fitrah Amalia Rahman, Miftahur Sanriomi Sintaro Sari, Priskila Lovika Setiawansyah Setiawansyah Sri Subanti Wang, Junhai yasin, ikbal Yosep Nuryaman Yuri Rahmanto