Article Per Year (5 Year)
p-Index From 2020 - 2025
3.302
P-Index
This Author published in this journals
All Journal Jurnal Teknik Komputer AMIK BSI METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi JIPN (Journal of Informatics Pelita Nusantara) METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Informatika Kaputama (JIK) TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Journal of Intelligent Decision Support System (IDSS) INFOKUM Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pengabdian kepada Masyarakat Nusantara KLIK: Kajian Ilmiah Informatika dan Komputer INFOSYS (INFORMATION SYSTEM) JOURNAL Jurnal Media Informatika Jurnal Info Sains : Informatika dan Sains
Jijon Raphita Sagala
STMIK Pelita Nusantara, Medan
Aerospace Engineering Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Neuroscience Social Sciences Transportation

Published : 26 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : KLIK: Kajian Ilmiah Informatika dan Komputer

 1 
Penerapan Data Mining Untuk Pengelompokan Siswa Berdasarkan Nilai Akademik dengan Algoritma K-Means Penda Sudarto Hasugian; Jijon Raphita Sagala
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 3 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i3.627

Abstract

The data mining process by applying the K-Means algorithm is carried out to group data into one or more groups, where data that has representative similarities is grouped into one group and data that has differences is included in another group. Grouping student data is done to facilitate schools in facilitating students based on differences in their ability to learn and participate in learning which consists of groups or classes of superior students, medium and low groups. The data application used for the calculation process is student data based on a centralized assessment in presenting reports on student learning outcomes using the results of report cards, namely the rapid miner. This assessment forms the basis of the attributes used in the calculation process to determine superior, medium and low class students. The purpose of this study is to manage centralized assessment data in presenting reports on student learning outcomes and grouping students in superior classes by implementing the K-means algorithm and conducting tests using the rapidminer application. So that student data can be managed and grouped effectively and efficiently
Co-Authors Amran Sitohang Devi Permata Sari Sianturi Dwi Putri Rahayu Fenda Sudarto Hasugian Hasanul Fahmi Hasanul Fahmi Hasugian , Paska Marto Hasugian, Penda Sudarto Insan Astuti Laphita Sari Simanjuntak Larisma Situmorang Lela Dwi Ani Martua Sitorus Mawaddah Arrosty Melisa Van Breukelen Mufida Khairani Murni Marbun Nicko Permana Putra Nuri Latifa Efrata Nurjamiyah, Nurjamiyah Nurmawaty Hutabarat Permata Sari Tarigan Sarah Afriani Sihombing Simangunsong, Agustina Sulindawaty, Sulindawaty Syahrul Fahri W. S. Usha Nantheni Yessy F A Lubis Yuda Perwira Zanma Ameta Tarigan