Attribute Selection Techniques to Clustering the Entrepreneurial Potential of Student based on Academic Behavior

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

A key factor in the process of knowledge discovery in databases is the quality of data that consists of a set of attributes that explain the characteristics of the data. For that, we need the right attribute selection method for optimal data mining performance. In this case, the attributes tested with machine learning are the result of mapping factors is affecting entrepreneurship of students based on behavioral science theory on the attributes of Indonesia Higher Education Database. Testing dataset attributes using four different methods, namely Correlation, Information Gain, OneR, and Relief F. The results of clustering experiments with the Simple K-Means algorithm show that OneR method decrease in the largest drop of Sum of Squared Errors (17%) compared to the other three methods. With the most important attribute differences in each attribute selection method, the instances cluster profile generated is also different.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538683446
DOIs
Publication statusPublished - Jun 2019
Externally publishedYes
Event24th Annual IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2019 - Tianjin, China
Duration: 14 Jun 201916 Jun 2019

Publication series

Name2019 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2019 - Proceedings

Conference

Conference24th Annual IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2019
Country/TerritoryChina
CityTianjin
Period14/06/1916/06/19

Keywords

  • academic behavior
  • attribute selection
  • clustering
  • entrepreneurial potential

Fingerprint

Dive into the research topics of 'Attribute Selection Techniques to Clustering the Entrepreneurial Potential of Student based on Academic Behavior'. Together they form a unique fingerprint.

Cite this