Rancang Bangun Sistem Pendukung Keputusan Seleksi Karyawan Dengan Metode Multi Attribute Utility Theory.

al wendi; lela budiarti; Andi saputra mandopa

doi:10.24929/jars.v3i2.4184

al wendi Universitas Graha Nusantara
lela budiarti Universitas Muhammadiyah Tapanuli Selatan
Andi saputra mandopa Universitas Graha Nusantara

DOI: https://doi.org/10.24929/jars.v3i2.4184

Keywords: Decision Support System, Design, Employee, MAUT Method.

Abstract

Decision making involving multiple criteria is often a challenge in the selection process, especially when having to choose the best alternative from a number of candidates. This study aims to build a Decision Support System (DSS) that is able to assist the selection process of the best candidates objectively, structured, and efficiently. The method used is the Multi-Attribute Utility Theory (MAUT), which has the ability to handle multi-criteria decision making with a utility approach, where each criterion is weighted based on its level of importance. This system is designed using the UML (Unified Modeling Language) modeling language to present a clear visual representation of the proposed system. The criteria used in the study consist of 5 criteria, namely: Work experience, education, age, status, and web address. Each alternative is assessed based on these five criteria, then the normalization process and calculation of the total utility value are carried out to determine the final ranking. The respondents or samples in this study consisted of 5 students registered in August 2024, from the five samples used, the highest utility result with code A02 in the name of Ahmad Suhery obtained the highest utility value of 0.6893, so that it was determined as the best alternative in the selection process. This system is expected to be a tool to assist in decision making.

References

[1] N. Tou, P. M. Endraswari, and Y. S. R. Nur, “Pemilihan Mahasiswa Berprestasi Menggunakan Metode AHP pada Fakultas Teknik Ubb,” JIKA (Jurnal Inform., vol. 7, no. 1, pp. 46–53, 2023.
[2] D. O. Sihombing and A. Cahyadi, “Implementasi Metode MABAC Dalam Pemilihan Mahasiswa Terbaik Dengan Teknik Pembobotan Rank Sum,” J. Comput. Syst. Informatics, vol. 4, no. 4, pp. 1008–1018, 2023, doi: 10.47065/josyc.v4i4.4040.
[3] H. B. Santoso, “Metode Pembobotan Simplified Pivot Pairwise Relative Criteria Importance Assessment dan COPRAS Dalam Penentuan Seleksi Penerimaan Guru,” J. Artif. Intell. Technol. Inf., vol. 1, no. 4, pp. 154–163, 2023.
[4] L. Cahyani, Mu. Arif, and F. Ningsih, “Sistem Pendukung Keputusan Pemilihan Mahasiswa Berprestasi Menggunakan Metode Moora (Studi Kasus Fakultas Ilmu Pendidikan Universitas Trunojoyo Madura,” J. Ilm. Edutic Pendidik. dan Inform., vol. 5, no. 2, pp. 108–114, 2019, [Online]. Available: https://journal.trunojoyo.ac.id/edutic/article/view/5354
[5] A. A. Wahid, “Analisis Metode Waterfall Untuk Pengembangan Sistem Informasi,” J. Ilmu-ilmu Inform. dan Manaj. STMIK, no. November, pp. 1–5, 2020.
[6] AKBAR, Niko. Perancangan Spk Tentang Keterampilan Mahasiswa Dengan Metode Saw. Rabit: Jurnal Teknologi dan Sistem Informasi Univrab, 2023, 8.1: 105-112.
[7] AL HARITS, Muhammad Yusuf; AL MAJID, Yusuf Fahrul. Sistem Pendukung Keputusan Pemilihan Beasiswa Pada Mahasiswa dengan Metode TOPSIS. Journal of Information Technology, 2023, 5.1: 27-32.
[8] MAYOLA, Liga, et al. Analytical Hierarchy Process (AHP) dalam Seleksi Penerimaan Mahasiswa Baru. Jurnal KomtekInfo, 2023, 81-86.
[9] DURUKA, Dian Safitri; RANSI, Natalis; SURIMI, La. SISTEM PENDUKUNG KEPUTUSAN PENENTUAN KUOTA PENERIMAAN MAHASISWA BARU MENGGUNAKAN METODE ANALYTIC HIERARCHY PROCESS. AnoaTIK: Jurnal Teknologi Informasi dan Komputer, 2023, 1.1: 9-14.
[10] MUNAWAROH, Mukminatul, et al. Analisis Sistem Pendukung Keputusan Menggunakan Algoritma AHP Dan Topsis Untuk Menentukan Mahasiswa Lulusan Terbaik. Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika, 2024, 2.1: 09-24.
[11] Nasution, M. I., Fadlil, A., & Sunardi, S. (2021). Perbandingan Metode Smart dan Maut untuk Pemilihan Karyawan pada Merapi Online Corporation. Jurnal Teknologi Informasi Dan Ilmu Komputer, 8(6), 1205-1214.
[12] Budiarti, L., & Nurcahyo, G. W. (2024). Penerapan Metode Jaringan Syaraf Tiruan Backpropagation Untuk Memprediksi Kualitas Makanan Kucing. Jurnal KomtekInfo, 390-397.
[13] Budiarti, L., & Mandopa, A. S. (2024). Sistem Pendukung Keputusan untuk Menentukan Mahasiswa Terbaik Menggunakan Metode Complex Proportional Assessment. SMART: Jurnal Teknologi Informasi dan Komputer, 3(2), 98-106.
[14] Mandopa, A., & Budiarti, L. (2024). APLIKASI DATA MINING UNTUK MENENTUKAN LULUSAN MAHASISWA TEPAT WAKTU. Journal of Advanced Research in Informatics, 3(1), 59-65.