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All Journal Jusikom : Jurnal Sistem Komputer Musirawas Journal of Artificial Intelligence and Digital Business Journal of Data Analytics, Information, and Computer Science (JDAICS) Prawara Jurnal Pengabdian Masyarakat Jurnal Informatika dan Rekayasa Perangkat Lunak
Sefrika, Sefrika
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mathematics Public Health Social Sciences Other

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Journal : Jurnal Informatika dan Rekayasa Perangkat Lunak

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Decision Support System for New Employee Admission Selection Using a Combination of LOPCOW and MARCOS Imron, Imron; Yulia, Eka Rini; Andriansah, Andriansah; Sefrika, Sefrika
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 1 (2025): Volume 6 Number 1 March 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v6i1.9

Abstract

The selection of new hires is an important process in human resource management to ensure that the organization gets the individuals who best suit the company's needs and goals. The main problem in the selection of new employee admissions is often related to the difficulty of achieving objectivity and fairness in the assessment process. Reliance on subjective assessment, lack of structured selection methods or absence of valid and reliable measurement tools can result in inaccurate decisions. The ranking results in the selection of new employee admissions show the value generated from each candidate, Candidate AE is ranked first with the highest score of 24.48, followed by Candidate DS with a score of 22.95. JE Candidate was ranked third with a score of 21.36, followed by FY Candidate with a score of 21.3. These results reflect the performance of each candidate in meeting the selection criteria that have been determined. This research contributes to improving accuracy and fairness in selection decision-making, by reducing subjectivity bias in weighting and ranking candidates. With transparent and measurable results, this research helps companies in systematically selecting the best candidates, while improving the efficiency and effectiveness of the recruitment process. The combination of the LOPCOW and MARCOS methods offers the flexibility to be applied in a variety of selection contexts, not only in employee admissions, but also in other multi-criteria decision-making.
Co-Authors Andriansah, Andriansah Apriyani, Helina Dara, Niken Ayu Eka Rini Yulia Hananda Priyandaru Imron Imron, Imron Maelani, Nova Dwi Nisah, Shifa Hairul Pambudi, Luhur Prasistia, Ajeng Priyanto, Satrio Nur Puspasari , Aprilia Puspasari, Aprilia Sifa Fauziah, Sifa Sismadi, Sismadi