Sistem Pendukung Keputusan Pemilihan Asisten Laboratorium Menggunakan Metode MABAC

Rili Aditya; Satrio Apriza Pradana; Wahyudi Maulana; Divi Handoko; David David

doi:10.70340/jirsi.v4i1.176

Authors

Rili Aditya Universitas Harapan Medan
Satrio Apriza Pradana Universitas Harapan Medan
Wahyudi Maulana Universitas Harapan Medan
Divi Handoko Universitas Harapan Medan
David David Universitas Harapan Medan

DOI:

https://doi.org/10.70340/jirsi.v4i1.176

Keywords:

Decision Support System, MABAC Method, Selection of laboratory assistants, Multi-criteria, decision-making

Abstract

The selection of the right laboratory assistant is very important to support practicum activities in the laboratory. The complex selection process requires a systematic approach to assessing candidates based on various criteria, such as GPA, semester specialty, programming knowledge test, interview test. The Multi-Attributive Border Approximation Area Comparison (MABAC) method is one of the methods in multi-criteria decision-making that can be used to solve this problem. MABAC offers an effective approach to evaluating and ranking candidates based on the weight of predetermined criteria. This study implements the MABAC method in SPK for the selection of laboratory assistants, with the aim of improving objectivity and accuracy in the selection process. The results of this system show that MABAC is able to provide consistent and reliable recommendations in determining the most suitable candidates as laboratory assistants.

Downloads

Download data is not yet available.

References

J. Banjarnahor, “Sistem Pendukung Keputusan Untuk Penentuan Asisten Laboratorium Komputer Dengan Metode TOPSIS Studi Kasus Laboratorium AMIK MBP,” vol. 1, no. 2, pp. 2798–9593, 2022, [Online]. Available: https://ejournal.amikmbp.ac.id/index.php/lofian/

D. J. Lubis and A. I. Ningtiyas, “Penerapan Metode Naïve Bayes Untuk Rekomendasi Pemilihan Asisten Laboratorium Komputer Di Perguruan Tinggi,” vol. 12, pp. 127–138, 2022, doi: 10.36350/jbs.v12i2.

S. S. C. A. Sri Liswardani, “14597-49793-1-SM,” Jurnal Pengelolaan Laboratorium Pendidikan, pp. 42–47, Jun. 2022.

R. T. Aldisa, “Penerapan Metode MABAC dalam Sistem Pendukung Keputusan Rekomendasi Aplikasi Pemesanan Hotel Terbaik,” Journal of Information System Research (JOSH), vol. 4, no. 1, pp. 191–201, Oct. 2022, doi: 10.47065/josh.v4i1.2415.

E. B. Barus, “Sistem Pendukung Keputusan Pemilihan Best Employee Dengan Menerapkan Metode MABAC,” TIN: Terapan Informatika Nusantara, vol. 2, no. 9, pp. 551–557, Feb. 2022, doi: 10.47065/tin.v2i9.1028.

K. Nisa, S. Informasi, and S. Triguna Dharma, “Nomor 2,” Volume, vol. 5, pp. 280–292, 2022, [Online]. Available: https://ojs.trigunadharma.ac.id/index.php/jsk/index

N. Hayati, S. Rahayu, T. Ichsan Saputra, and U. Nasional, “STRING (Satuan Tulisan Riset dan Inovasi Teknologi) SISTEM INFORMASI PEMILIHAN ASISTEN LABORATORIUM DENGAN METODE WEIGHTED PRODUCT DAN WEIGHTED SUM MODEL.”

N. Ndruru, F. Tinus Waruwu, and D. Putro Utomo, “RESOLUSI : Rekayasa Teknik Informatika dan Informasi Penerapan Metode MABAC Untuk Mendukung Pengambilan Keputusan Pemilihan Kepala Cabang Pada PT. Cefa Indonesia Sejahtera Lestari,” Media Online), vol. 1, no. 1, pp. 36–49, 2020, [Online]. Available: https://djournals.com/resolusi

M. Daffa Saefudin and A. Mirza, “OKTAL : Jurnal Ilmu Komputer dan Sains Sistem Penunjang Keputusan Penilaian Guru Terbaik Dengan Metode Multi-Attributive Border Approximation (MABAC),” 2022. [Online]. Available: https://journal.mediapublikasi.id/index.php/oktal

A. Ahyuna, B. Rahman, F. Nugroho, I. W. S. Nirawana, and A. Karim, “Analisa Penerapan Metode MABAC dengan Pembobotan Entropy dalam Penilaian Kinerja Dosen di Era Society 5.0,” Building of Informatics, Technology and Science (BITS), vol. 5, no. 1, Jun. 2023, doi: 10.47065/bits.v5i1.3511.