Rekomendasi Paket Mata Pelajaran Pilihan (MPP) pada SMA Negeri 1 Kebumen Menggunakan Algoritma K-means

• Published in: Jurnal Informatika dan Rekayasa Perangkat Lunak (Online) Vol. 5; no. 2; pp. 96 - 103
• Main Authors: Trisnapradika, Gustina Alfa, Ghozi, Wildanil, Yuminah, Yuminah
• Format: Journal Article
• Language: English; Indonesian
• Published: Universitas Wahid Hasyim 09.10.2023
• Subjects: data mining, unsupervised learning, clustering, k-means
• ISSN: 2656-2855; 2685-5518
• DOI: 10.36499/jinrpl.v5i2.8514

Curriculum changes are needed to adapt education to the times. Since the covid-19 pandemic, face-to-face learning has been suspended. Online learning is an alternative used during a pandemic. This has an impact on learning loss so that the quality of learning decreases. Recovery of learning during the pandemic and post-pandemic Covid-19 is important to reduce the impact of learning loss on students. After the pandemic, the independent curriculum was launched which was a refinement of the 2013 curriculum which had only been implemented in several schools. The subject structure of the Merdeka curriculum for SMA level in Fese E or grade 10, all students get the same subjects. While in Phase F (grades 11 and 12), the subject structure is divided into 2 main groups, namely general subjects and elective subjects. Based on the provisions of the SMKA 2021-2022 curriculum structure, SMA Negeri 1 Kebumen prepares elective subjects (MPP) which are made up of 7 MPP packages. This study uses a clustering technique of student scores using the K-Means algorithm to obtain MPP package recommendations that suit student abilities. For each MPP package, clustering is carried out into 2 clusters with features in the form of predetermined subject scores. The result of this clustering is that each student gets a "yes" or "no" recommendation for each MPP package.