Decision Support System for Performance Assessment of Honoray Personnel Applying MABAC, MOORA, and ARAS Method with a Combination of ROC Weighthing

Authors

  • Woro Agus Nurtiyanto Informatics Engineering Study Program, Faculty of Computer Science, Pamulang University
  • Perani Rosyani Informatics Engineering Study Program, Faculty of Computer Science, Pamulang University
  • Ines Heidiani Ikasar Informatics Engineering Study Program, Faculty of Computer Science, Pamulang University
  • Muhammad Syam Noverick Informatics Engineering Study Program, Faculty of Computer Science, Pamulang University
  • Galuh Surya Permana Informatics Engineering Study Program, Faculty of Computer Science, Pamulang University
  • Bagus Wicaksono Informatics Engineering Study Program, Faculty of Computer Science, Pamulang University

DOI:

https://doi.org/10.55927/ijis.v2i12.7378

Keywords:

DSS (Decision Support System), MABAC, MOORA, ARAS

Abstract

MABAC (Multi-Attributive Border Approximation area Comparison), ARAS (Additive Ratio Assessment), and MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) are decision support system methods employed for evaluating the performance of honorary staff. MABAC utilizes a multi-attribute border approximation area approach to measure the relative performance of honorary staff. ARAS assigns weights to competing attributes and produces assessment ratio values aiding in decision-making. Meanwhile, MOORA focuses on multi-objective optimization by considering ratio analysis. The combination of these three methods provides a holistic and comprehensive framework for assessing the performance of honorary staff, enabling decision-makers to effectively evaluate their contributions and achievements based on predefined criteria. This approach allows for the determination of relative rankings and the selection of honorary staff that best align with organizational needs

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References

Anas. (2019). Menggunakan Metode Additive Ratio Assessment ( Aras ). Universitas Ichsan Gorontalo, 4(1), 1–5.

Arista, R. D., Defit, S., & Yunus, Y. (2020). MOORA sebagai SistemPendukung Keputusan Dalam Mengukur Tingkat Kinerja Dosen (Universitas Pembangunan Panca Budi Medan). Jurnal Informatika Ekonomi Bisnis, 2, 104–110. https://doi.org/10.37034/infeb.v2i4.52

Chamid, A. A. (2018). Prioritas Kondisi Rumah. Jurnal Simetris, 7(2), 537–544.

Munthe, K., Syahputra, T. R. A., Pasuli, A. A., & Hasibuan, M. A. (2022). Sistem Pendukung Keputusan Pemilihan Pegawai Honorer Kelurahan Medan Sinembah Menerapkan Metode ROC dan MOORA. Bulletin of Informatics …, 1(1). https://ejurnal.pdsi.or.id/index.php/bids/article/view/5%0Ahttps://ejurnal.pdsi.or.id/index.php/bids/article/download/5/4

Nadeak, A. S. (2019). Penerapan Metode Aras ( Additive Ratio Assessment ) Dalam Penilaian Guru Terbaik. Seminar Nasional Teknologi Komputer & Sains (SAINTEKS), 2(2010), 571–578.

oktavian 2018. (2018). Bab II Landasan Teori. Journal of Chemical Information and Modeling, 53(9), 1689–1699.

Saprudin, Nurjaya, & Herdiansyah, R. (2019). Sistem Penunjang Keputusan. In Journal of Chemical Information and Modeling (Vol. 53, Issue 9).

Sri Agustiani Br Siburian, Mohammad Taufan Asri Zaen, Setiawansyah, Dodi Siregar, Erlin Windia Ambarsari, & Yuwan Jumaryadi. (2023). Penerapan Metode Additive Ratio Assement (ARAS) dalam Pemilihan Customer Service Terbaik. Journal of Informatics Management and Information Technology, 3(1), 12–17. https://doi.org/10.47065/jimat.v3i1.239

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Published

2023-12-28

How to Cite

Woro Agus Nurtiyanto, Perani Rosyani, Ines Heidiani Ikasar, Muhammad Syam Noverick, Galuh Surya Permana, & Bagus Wicaksono. (2023). Decision Support System for Performance Assessment of Honoray Personnel Applying MABAC, MOORA, and ARAS Method with a Combination of ROC Weighthing . International Journal of Integrative Sciences, 2(12), 2067–2086. https://doi.org/10.55927/ijis.v2i12.7378