IJIIS: International Journal of Informatics and Information Systems
Vol 1, No 1: September 2018

Application of Data Mining Classification Method for Student Graduation Prediction Using K-Nearest Neighbor (K-NN) Algorithm

Mohammad Imron (Amikom University Purwokerto, Indonesia)
Satia Angga Kusumah (Amikom University Purwokerto, Indonesia)

Article Info

Publish Date
01 Sep 2018

Abstract

The student graduation rate is one of the indicators to improve the accreditation of a course. It is needed to monitor and evaluate student graduation tendencies, timely or not. One of them is to predict the graduation rate by utilizing the data mining technique. Data Mining Classification method used is the algorithm K-Nearest Neighbor (K-NN). The data used comes from student data, student value data, and student graduation data for the year 2010-2012 with a total of 2,189 records. The attributes used are gender, school of origin, IP study program Semester 1-6. The results showed that the K-NN method produced a high accuracy of 89.04%.

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Journal Info
IJIIS: International Journal of Informatics and Information Systems
Website

Abbrev

IJIIS

Publisher

Bright Publisher

Subject

Computer Science & IT

Description

The IJIIS is an international journal that aims to encourage comprehensive, multi-specialty informatics and information systems. The Journal publishes original research articles and review articles. It is an open access journal, with free access for each visitor (ijiis.org/index.php/IJIIS/); ...