TELKOMNIKA Telecommunication, Computing, Electronics and Control
Enhancement of student performance prediction using modified K-nearest neighbor

Dublin Core

Title

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Enhancement of student performance prediction using modified K-nearest neighbor

Subject

Consuming time, Educational data mining, Moments, KNN, Prediction

Description

The traditional K-nearest neighbor (KNN) algorithm uses an exhaustive search for a complete training set to predict a single test sample. This procedure can slow down the system to consume more time for huge datasets. The selection of classes for a new sample depends on a simple majority voting system that does not reflect the various significance of different samples (i.e. ignoring the similarities among samples). It also leads to a misclassification problem due to the occurrence of a double majority class. In reference to the above-mentioned issues, this work adopts a combination of moment descriptor and KNN to optimize the sample selection. This is done based on the fact that classifying the training samples before the searching actually takes place can speed up and improve the predictive performance of the nearest neighbor. The proposed method can be called as fast KNN (FKNN). The experimental results show that the proposed FKNN method decreases original KNN consuming time within a range of (75.4%) to (90.25%), and improve the classification accuracy percentage in the range from (20%) to (36.3%) utilizing three types of student datasets to predict whether the student
can pass or fail the exam automatically.

Creator

Saja Taha Ahmed, Rafah Al-Hamdani, Muayad Sadik Croock

Source

DOI: 10.12928/TELKOMNIKA.v18i4.13849

Publisher

Universitas Ahmad Dahlan

Date

August 2020

Contributor

Sri Wahyuni

Rights

ISSN: 1693-6930

Relation

http://journal.uad.ac.id/index.php/TELKOMNIKA

Format

PDF

Language

English

Type

Text

Coverage

TELKOMNIKA Telecommunication, Computing, Electronics and Control

Files

Collection

Tags

,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon ,

Citation

Saja Taha Ahmed, Rafah Al-Hamdani, Muayad Sadik Croock, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Enhancement of student performance prediction using modified K-nearest neighbor,” Repository Horizon University Indonesia, accessed November 14, 2024, https://repository.horizon.ac.id/items/show/3933.