International Journal of Electrical and Computer Engineering
Vol 10, No 5: October 2020

Data science for digital culture improvement in higher education using K-means clustering and text analytics

Dian Sa'adillah Maylawati (UIN Sunan Gunung Djati Bandung, and Universiti Teknikal Malaysia Melaka)
Tedi Priatna (UIN Sunan Gunung Djati Bandung)
Hamdan Sugilar (UIN Sunan Gunung Djati Bandung)
Muhammad Ali Ramdhani (UIN Sunan Gunung Djati Bandung)



Article Info

Publish Date
01 Oct 2020

Abstract

This study aims to investigate the meaningful pattern that can be used to improve digital culture in higher education based on parameters of the technology acceptance model (TAM). The methodology used is the data mining technique with K-means algorithm and text analytics. The experiment using questionnaire data with 2887 respondents in Universitas Islam Negeri (UIN) Sunan Gunung Djati Bandung. The data analysis and clustering result show that the perceived usefulness and behavioral intention to use information systems are above the normal value, while the perceived ease of use and actual system use is quite low. Strengthened with text analytics, this research found that the EDA and K-means result in harmony with the hope or desire of academic society the information system implementation. This research also found how important the socialization and guidance of information systems, especially the new one information system, in order to improve digital culture in higher education.

Copyrights © 2020






Journal Info

Abbrev

IJECE

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of ...