Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Informatika dan Rekayasa Perangkat Lunak
Yuminah Yuminah
SMA Negeri 1 Kebumen
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Rekomendasi Paket Mata Pelajaran Pilihan (MPP) pada SMA Negeri 1 Kebumen Menggunakan Algoritma K-means Gustina Alfa Trisnapradika; Wildanil Ghozi; Yuminah Yuminah
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 5, No 2 (2023): September
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v5i2.8514

Abstract

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.
Co-Authors Gustina Alfa Trisnapradika Wildanil Ghozi