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Pasaribu, A. Ferico Octaviansyah
Fakultas Teknik Dan Ilmu Komputer, Universitas Teknokrat Indonesia
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Journal : Bulletin of Computer Science Research

 1 
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.
Co-Authors Ade Dwi Putra ade rahman Ade Surahman Ade Surahman Adhie Thyo Priandika Adi Sucipto, Adi Agus Irawan Ahmad Ari Aldino Aldi Bagus Prasetyo Amik Herningsih Andi Nurkholis Arif Febriansyah Arifin Nur Dedi Darwis Dedi Darwis Dedi Irawan Depriansah Depriansah Donaya Pasha Eka Shintya Pratiwi Fachrul Kurnia Adam Farid Jack Hendri Farid Jeck Fikri Hamidy Fredy Hermawan Gufran Umar, M. Kasyif Habib Rizki A.Siregar Imam Ahmad Irna Puspasari Kadek Dwi Riska Santi Kiki Septiani Leny Meilisa M. Rizky Fadhilah Mahdalena Serumpun Maria Ainun Nazar Maulana Aziz Assuja Muhammad Al Khusnul Rizki Nita Afriani Novi Eka Wati Nurfitria Ningsi Nuroji Nuroji Nuroji Nuroji Oprasto, Raditya Rimbawan Permata, Permata Prasetyo, Aditya Dwi Purnomo Aji Renaldy Hermanto Renaldy Hermanto Riska Aryanti Riskiono, Sampurna Dadi Sampurna Dadi Riskiono Sanriomi Sintaro Saputra, Febrian Eko Setiawan, Gde Denny Setiawansyah Setiawansyah Shinta Bela Siti Romlah Sumanto, Sumanto Surahman, Ade Vera Nadita Very Hendra Saputra vista anestiviya Wahyudi Wahyudi Wahyudi, Agung Deni Wang, Junhai YOHANA TRI UTAMI, YOHANA TRI Yopita Anggela Yuri Rahmanto Yusra Fernando Yusra Fernando