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All Journal Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika Jurnal Teknik Informatika UNIKA Santo Thomas MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Mantik KAKIFIKOM : Kumpulan Artikel Karya Ilmiah Fakultas Ilmu Komputer Jatilima : Jurnal Multimedia Dan Teknologi Informasi INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) MEANS (Media Informasi Analisa dan Sistem) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Info Sains : Informatika dan Sains Jurnal Pengabdian Masyarakat IPTEK Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Armada Informatika Jurnal Masyarakat Indonesia Journal of Blockchain, Nfts and Metaverse Technology "Journal of Data Science
Simangunsong, Pandi Barita Nauli
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Other

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Journal : "Journal of Data Science

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Testing the K-Means Clustering Algorithm in Processing Student Assignment Grades Using the RapidMiner Application Simangunsong, Pandi Barita Nauli; Manalu, Mamed Rofendi
Journal Of Data Science Vol. 1 No. 02 (2023): Journal Of Data Science, September 2023
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/jds.v1i02.2838

Abstract

In the current era of computers and the internet, educational data analysis has become very important to optimize the teaching and learning process. This study focuses on the use of the K-Means clustering algorithm used by the RapidMiner application to group assignment grades given to students during one academic semester. The goal is to discover patterns of achievement and areas that require intervention. The results show that the algorithm is very effective in identifying groups of students based on their performance and dividing them into middle, high, and those who need help. In short, the use of K-Means Clustering with RapidMiner offers a useful analytical approach for education. This allows for a more customized learning approach that is based on analysis of student achievement.
Co-Authors Alex Rikki Arisman Ayuningsih, Ekatri Barus, Apriwati Devri Suherdi Fithrie Soufitri Fitri, Komariah Furqan Ginting, Erika Fahmi Hasugian , Paska Marto Indra Sidabutar Irwan Jani Tarigan kamil erwansyah Lintang Patria M.Rajagukguk, Denni Makmur Tarigan Mamed Rofendy Manalu Manalu, Mamed Rofendi Mathelinea, Devy Matias Julyus Fika Sirait Maulidina Monang Juanda Tua Sihombing Muhammad Amin Muhammad Amin Nasib Marbun Panjaitan, Muhammad Iqbal Pristiwanto Rita Hamdani Siagian, Novriadi Antonius Simamora, Siska Simatupang, Baharis Setia Adisahputra Simbolon, Hasanal Fachri Satia Sitompul, Bernad J. D. Sitorus, Syahrial Sony Bahagia Sinaga Sridewi, Nurmala Syarifah Fadillah Rezky Tuti Andriani Tuti Andriani Yati, Nurhayati