Jurnal Manajemen dan Teknologi Informasi
Vol. 13 No. 2 (2023): Jurnal Manajemen dan Teknologi Informasi

DATA MINING MEMPREDIKSI KELULUSAN MAHASISWA MENGGUNAKAN METODE K-NEAREST NEIGHBORS (KNN) STUDI KASUS UNIVERSITAS PGRI MAHADEWA INDONESIA

I Putu Yogista Putra Atmaja (Universitas PGRI Mahadewa Indonesia)
Gde Iwan Setiawan (Univeristas PGRI Mahadewa Indonesia)
I Wayan Dika (Univeristas PGRI Mahadewa Indonesia)
Ida Ayu Putu Febri Imawati (Univeristas PGRI Mahadewa Indonesia)

Article Info

Publish Date
26 Oct 2023

Abstract

Graduation is a significant milestone in education, and it is a crucial assessment factor for ensuring higher education accreditation. The K-Nearest Neighbor (KNN) algorithm classifies objects based on learning data, with a minimum and maximum number of training datasets. The algorithm normalizes patterns, calculates Euclidean distance, votes from the smallest euclidean distance, and determines the classification results. The Student Graduation Prediction Model uses the KNN method to help assess students' graduation accuracy and accreditation.

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Journal Info
Jurnal Manajemen dan Teknologi Informasi
Website

Abbrev

jmti

Publisher

Universitas PGRI Mahadewa Indonesia

Subject

Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering

Description

”Jurnal Manajemen dan Teknologi Informasi adalah jurnal ilmiah yang dikelola oleh Fakultas Teknologi dan Informasi PGRI Mahadewa Indonesia”. Jurnal ini berisi makalah hasil penelitian yang mencakup bidang komputer secara umum yaitu Sistem Informasi Sistem Komputer Ilmu Komputer atau Informatika ...