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All Journal Journal of Economics, Business, & Accountancy Ventura DEDIKASI JURNAL MAHASISWA MediaKom : Jurnal Ilmiah Ilmu Komunikasi Konvergensi : Jurnal Ilmiah Ilmu Komunikasi Jurnal Universitas Paramadina Turbo : Jurnal Program Studi Teknik Mesin Jurnal Daur Lingkungan SKANIKA: Sistem Komputer dan Teknik Informatika STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Frasa: Jurnal Keilmuan Bahasa, Sastra dan pengajarannya
Suraya Suraya
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Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences

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Journal : SKANIKA: Sistem Komputer dan Teknik Informatika

 1 
PENERAPAN METODE CLUSTERING DENGAN ALGORITMA K-MEANS PADA PENGELOMPOKAN INDEKS PRESTASI AKADEMIK MAHASISWA Suraya Suraya; Muhammad Sholeh; Dina Andayati
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 6 No 1 (2023): Jurnal SKANIKA Januari 2023
Publisher : Fakultas Teknologi Informasi, Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v6i1.2982

Abstract

The process of evaluating student academic achievement results is needed as an effort to monitor student academic development. Grouping students according to the results of academic achievement is needed. One of the uses is as a mapping process for students who can be expected to graduate on time and students whose grades are still low so that assistance is needed. The purpose of this grouping can be used as a student achievement index mapping. The research conducted aims to provide an alternative grouping of academic achievement based on the data mining process using a clustering model. The research method uses the Knowledge Discovery in Database method. The data mining method with Knowledge Discovery in Database consists of selection, pre-processing, transformation, model and evaluation. The datasheet used is a collection of student achievement index data processed from the acquisition of student achievement index in semester 1 to 6. The clustering model is built using the K-Means algorithm. The results of the study resulted in the best grouping is grouping as much as 2, The process of getting the best grouping is done by testing the model with 6 groupings. The best grouping results are done with Davies Bouldin testing. The conclusion of the study with the results of the 2 groups can be given a category, cluster 0 with the name of the good category and cluster 1 with the category not good.
Co-Authors Abdul Hafid Brian Andika Dina Andayati Eko Nugroho Hadrah Hadrah Ismail Marzuki Kemas Ridhuan Monik Kasman Muhamad Nur Ichsanudin Muhammad Sholeh MUHAMMAD YUSUF Radik Sahaja Uminingsih Yakub Layuk Paembonan