NDLI: Comparison analysis of data mining methodology and student performance improvement influence factors in small data set

Content Provider	IEEE Xplore Digital Library
Author	Maharani, Kartika Adji, Teguh Bharata Setiawan, Noor Akhmad Hidayah, Indriana
Copyright Year	2015
Description	Author affiliation: Department of Electrical Engineering and Information Technology Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia (Maharani, Kartika; Adji, Teguh Bharata; Setiawan, Noor Akhmad; Hidayah, Indriana)
Abstract	Based on Programme for International Student Assessment survey, Indonesia student performance was on the lower position compared to other participated countries. Nevertheless, the actual reason of someone's performance in studying is hard to predict. Therefore, we need to limit the research's scope for finding more specific influencing factors. In this study, a group of students who have the same learning method, teacher, course, and also facility in a learning environment is observed to find significant influencing factors. We develop a questionnaire with various factors that are related to students' characteristic. It is administered to students of Junior High School Muhammadiyah 2 Depok Sleman in the same year. Consequently, data gathered is in small size. In order to yield maximum accuracy in small dataset, SMOTE is used to generate new data synthetically hence instance number is increasing. Besides several approaches were analyzed by using combination of preprocessing and variation feature selections. The result of this research shows that attribute subset selection by Classifier Subset Evaluator (CSE) yields the best result based on Naive Bayes accuracy and variance. Various significant factors influencing studying performance of tested students were also found including blood type, who student live with, father's education, mother's education, kind of activity done in spare time and favorite course.
Starting Page	169
Ending Page	174
File Size	603853
Page Count	6
File Format	PDF
ISBN	9781479983841
e-ISBN	9781479983865
DOI	10.1109/ICSITech.2015.7407798
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-27
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Learning systems Feature selection SMOTE Education Data preprocessing Data mining Naive bayes Information technology Classifier subset evaluator Blood Gain ratio Principal component analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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