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Sistem rekomendasi peminatan peserta didik baru pada kurikulum K-13 menggunakan metode profile matching, simple additive weighting, dan kombinasi keduanya

Recommender systems for specializing new students in the K-13 curriculum using the profile matching, SAW, and a combination of both

Master of Informatics, Universitas Islam Negeri Sunan Kalijaga Yogyakarta, Jl. Marsda Adisucipto Yogyakarta 55281, Indonesia

Received: 6 Sep 2020; Revised: 28 Dec 2020; Accepted: 26 Feb 2021; Available online: 20 Apr 2021; Published: 30 Apr 2021.
Open Access Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
The selection of students' interests based on the 2013 curriculum (K-13) is carried out before students start learning in class X. Accuracy in its determination is required to ensure that students learn according to their interests and talents. This study applies three DSS methods, namely profile matching, SAW, and a combination of both, to provide accurate recommendations for determining these students' interests. The three methods are compared using the same alternatives and criteria to find the most dominant method. The results of this study indicate that the application of SPK can assist PPDB activities with an accuracy of 79.2 %. In determining interest for students, the combination method is the most dominant, with an accuracy of 78 %. The application of DSS not only helps the specialization process to be faster but also accurate. This is indicated by only 6 out of 122 students who chose specialization based on the DSS recommendation getting a score below the KKM.
Keywords: K-13 curriculum; DSS; profile matching; SAW; specialization
Funding: Universitas Islam Negeri Sunan Kalijaga Yogyakarta

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