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Gede Surya Mahendra
Eddy Hartono

Abstract

To improve the quality and quality of employment, OJT is very much needed by Monarch Bali students, but the process, which is still manual, makes decisions that are taken less fast, accurate, effective and efficient. In line with the roadmap of Monarch Bali, it is necessary to develop an automation system to be able to improve the performance of decision making for OJT student placement by making a DSS. The method used in this research is AHP-MAUT and AHP-PM. The decision makers in this study were 3 people, and out of a total of 500 OJT students, 8 OJT students for F&B class, 12 OJT students for Housekeeping class, 13 OJT students for Catering class, and 17 OJT students for Food Management class with a total of 50 OJT students. In this study, AHP-MAUT and AHP-PM can be used properly and can be implemented into a web-based software which is quite user-friendly to users. Implementation of AHP-MAUT, OJT students from the Food Processing class with the code StudentD04 have the highest preference value of 0.5724, and OJT students from the F&B class with the code StudentA02 have a preference value of 4.1155 calculated using AHP-PM, each being ranked first.

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How to Cite
Mahendra, G. S., & Hartono, E. . (2021). Implementation of AHP-MAUT and AHP-Profile Matching Methods in OJT Student Placement DSS. Jurnal Teknik Informatika C.I.T Medicom, 13(1), 13–22. https://doi.org/10.35335/cit.Vol13.2021.56.pp13-22
References
I. W. W. Karsana, I. M. Candiasa, and G. R. Dantes, “Perencanaan Strategis Sistem Informasi dan Teknologi Informasi Menggunakan Framework Ward and Peppard pada Sekolah Bali Kiddy,” Jurnal Rekayasa Teknologi Informasi, vol. 3, no. 1, pp. 30–37, 2019.
Y. F. P. Toreh, “Analisis Penyerapan Tenaga Kerja Sektor Pariwisata di Provinsi Kepulauan Riau Tahun 2012 - 2017,” Jurnal Ilmiah Mahasiswa FEB, vol. 8, no. 1, pp. 1–15, 2019.
Y. W. S. Nugraha, “Monarch Bali,” 2018, [Online]. Available: http://monarchbali.com:3001/about.
G. S. Mahendra and I. P. Y. Indrawan, “Metode AHP-TOPSIS Pada Sistem Pendukung Keputusan Penentuan Penempatan Atm,” JST (Jurnal Sains dan Teknologi), vol. 9, no. 2, pp. 130–142, 2020, doi: 10.23887/jst-undiksha.v9i2.24592.
J. E. Leal, “AHP-express: A simplified version of the analytical hierarchy process method,” MethodsX, vol. 7, no. 1, pp. 1–24, 2020, doi: 10.1016/j.mex.2019.11.021.
D. N. Ilham and S. Mulyana, “Sistem Pendukung Keputusan Kelompok Pemilihan Tempat PKL Mahasiswa dengan Menggunakan Metode AHP dan Borda,” IJCCS, vol. 11, no. 1, pp. 55–66, 2017.
A. Alinezhad and J. Khalili, New Methods and Applications in Multiple Attribute Decision Making (MADM), 1st ed. Switzerland: Springer, 2019, p. 236.
T. Limbong and J. Simarmata, “Menentukan Matakuliah yang Efektif Belajar Daring (Belajar dan Ujian) dengan Metode Multi-Attribute Utility Theory (MAUT),” Jurnal RESTI, vol. 4, no. 2, pp. 370–376, 2020.
A. A. T. Susilo, “Penerapan Metode Profile Matching pada Sistem Pendukung Keputusan Pemilihan Ketua Program Studi (Studi Kasus : Program Studi Teknik Informatika STIMIK Musi Rawas),” JUITA, vol. 5, no. 2, pp. 87–93, 2017.
I. Fahmi, F. Kurnia, and G. E. S. Mige, “Perancangan Sistem Promosi Jabatan Menggunakan Kombinasi Analytical Hierarchy Process (AHP) Dan Profile Matching (PM),” Jurnal SPEKTRO, vol. 2, no. 1, pp. 26–34, 2019.
A. Febriantoko, “Analisis Efektivitas Program Latihan Kerja Sebagai Metode Penerimaan Karyawan (Studi Kasus Pada PT Unilever, Tbk., Indonesia),” 2008.
W. D. M. Nainggolan, B. S. Sunuharyo, and E. K. Aini, “Pengaruh On the Job Training dan Off the Job Traning Terhadap Kijerja Karyawan,” Jurnal Administrasi Bisnis, vol. 60, no. 1, pp. 112–119, 2018.
Ismail, Hasan, and Musdalifah, “Pengembangan Kompetensi Mahasiswa Melalui Efektivitas Program Magang Kependidikan,” Edumaspul - Jurnal Pendidikan, vol. 2, no. 1, pp. 124–132, 2018, doi: 10.33487/edumaspul.v2i1.48.
J. E. S. Casym and D. N. Oktiara, “Aplikasi Analytical Hierarchy Process dalam Mengidentifikasi Preferensi Laptop Bagi Mahasiswa,” 2020, pp. 636–640.
F. Rahman, M. T. Furqon, and N. Santoso, “Sistem Pendukung Keputusan Penentuan Prioritas Perbaikan Jalan Menggunakan Metode AHP-TOPSIS (Studi Kasus: Dinas Pekerjaan Umum dan Penataan Ruang Kabupaten Ponorogo),” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 2, no. 11, pp. 4365–4370, 2018.
R. Ramadiani and A. Rahmah, “Sistem Pendukung keputusan pemilihan tenaga kesehatan teladan menggunakan metode Multi-Attribute Utility Theory,” Jurnal Ilmiah Teknologi Sistem Informasi, vol. 5, no. 1, pp. 1–12, 2019.
R. Dhenabayu and A. Zainudin, “Penerapan Metode Profile Matching pada Sistem Pendukung Keputusan Performa Produksi Burung Puyuh,” Antivirus, vol. 11, no. 2, pp. 81–96, 2017.
Moreira, M. W., Rodrigues, J. J., Korotaev, V., Al-Muhtadi, J., & Kumar, N. (2019). A comprehensive review on smart decision support systems for health care. IEEE Systems Journal, 13(3), 3536-3545.
Demong, N. A. R. (2020). Data-driven Adaptive Personalized Property Investment Risk Analysis: Frameworks, Methods and System (Doctoral dissertation).
da Silva, L. B. L., Humberto, J. S., Alencar, M. H., Ferreira, R. J. P., & de Almeida, A. T. (2020). GIS-based multidimensional decision model for enhancing flood risk prioritization in urban areas. International Journal of Disaster Risk Reduction, 48, 101582.
Dellermann, D., Lipusch, N., Ebel, P., & Leimeister, J. M. (2019). Design principles for a hybrid intelligence decision support system for business model validation. Electronic markets, 29(3), 423-441.
Kukar, M., Vračar, P., Košir, D., Pevec, D., & Bosnić, Z. (2019). AgroDSS: A decision support system for agriculture and farming. Computers and Electronics in Agriculture, 161, 260-271.
Yuan, J., Li, X., Xu, C., Zhao, C., & Liu, Y. (2019). Investment risk assessment of coal-fired power plants in countries along the Belt and Road initiative based on ANP-Entropy-TODIM method. Energy, 176, 623-640.
Ijadi Maghsoodi, A., Ijadi Maghsoodi, A., Poursoltan, P., Antucheviciene, J., & Turskis, Z. (2019). Dam construction material selection by implementing the integrated SWARA—CODAS approach with target-based attributes. Archives of Civil and Mechanical Engineering, 19, 1194-1210.
Wu, Y., Zhang, T., Xu, C., Zhang, X., Ke, Y., Chu, H., & Xu, R. (2019). Location selection of seawater pumped hydro storage station in China based on multi-attribute decision making. Renewable energy, 139, 410-425.
Dehraj, P., & Sharma, A. (2020). An empirical assessment of autonomicity for autonomic query optimizers using fuzzy-AHP technique. Applied Soft Computing, 90, 106137.
Zhou, J., Wu, Y., Tao, Y., Gao, J., Zhong, Z., & Xu, C. (2021). Geographic information big data-driven two-stage optimization model for location decision of hydrogen refueling stations: An empirical study in China. Energy, 120330.