Recommendations for Placement of Internships in Industry with the Distance from Average Solution (EDAS) method  based on student scores

Tomy Satria Alasi; murdani murdani

Tomy Satria Alasi STMIK Logika
murdani murdani Universitas Budi Darma

Keywords: Recommendations, Placement Industry, Student Intern, EDAS Method.

Abstract

Currently, the Indonesian Ministry of Education has implemented a new rule with every student expected to have an internship in the industry. With the aim of each student being able to understand the situation of the world of work so that preparation before completing a bachelor's degree is stronger. However, one of the problems found is that students cannot determine the placement of internships. This study tries to provide a solution to these problems by applying the rules from the head of the study program to provide recommendations to students. These rules are built based on student academic scores stored in the campus database which is controlled by the head of the study program. The method used is Distance from Average Solution (EDAS). The EDAS method is to determine the highest ranking using PDA is the positive distance from the average and (NDA) is the negative distance from the average. The results of this study provide recommendations automatically in the hope of supporting the current campus academic system.

Downloads

Download data is not yet available.

References

D. Ivajnšič, D. Pintarič, V. J. Grujić, and I. Žiberna, “A spatial decision support system for traffic accident prevention in different weather conditions,” Acta Geogr. Slov., vol. 61, no. 1, pp. 75–92, 2021.

P. M. Hasugian, “Perancangan Sistem Pendukung Keputusan Dalam Menentukan Dosen Berprestasi Dengan Metode Simple Additive Weighting,” J. Inform. Pelita Nusant., vol. 4, no. 1, 2019.

L. T. Sianturi and others, “THE APPLICATION OF THE WASPAS METHOD WITH THE SWARA WEIGHTING METHOD APPROACH IN THE SELECTION OF SINGLE COLLEGE MONEY AID BUDIDARMA UNIVERSITY,” INFOKUM, vol. 9, no. 2, June, pp. 387–393, 2021.

P. Fitriani and T. S. Alasi, “Sistem Pendukung Keputusan dalam Menentukan Judul Skripsi Mahasiswa dengan Metode WASPAS, COPRAS dan EDAS berdasarkan Penilaian Dosen,” J. MEDIA Inform. BUDIDARMA, vol. 4, no. 4, pp. 1051–1061, 2020.

S. Arena, E. Florian, I. Zennaro, P. F. Orrù, and F. Sgarbossa, “A novel decision support system for managing predictive maintenance strategies based on machine learning approaches,” Saf. Sci., vol. 146, p. 105529, 2022.

P. dan S. S. Aggarwal Lakshita dan Goswami, “Sistem pendukung keputusan cerdas multi-kriteria untuk COVID-19,” Komputasi Lunak Terapan, vol. 101. .

R. Chinram, A. Hussain, T. Mahmood, and M. I. Ali, “EDAS method for multi-criteria group decision making based on intuitionistic fuzzy rough aggregation operators,” IEEE Access, vol. 9, pp. 10199–10216, 2021.

M. K. Ghorabaee, M. Amiri, E. K. Zavadskas, Z. Turskis, and J. Antucheviciene, “A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria,” J. Air Transp Manag., vol. 63, pp. 45–60, 2017.

P. Fitriani and T. S. Alasi, Sistem Pendukung Keputusan dengan Metode WASPAS, COPRAS dan EDAS: Menentukan Judul Skripsi Mahasiswa. Yayasan Kita Menulis, 2020.

M. Keshavarz Ghorabaee, M. Amiri, E. K. Zavadskas, Z. Turskis, and J. Antucheviciene, “A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria,” J. Air Transp. Manag., vol. 63, 2017, doi: 10.1016/j.jairtraman.2017.05.008.