Work

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

Year: 2020

Type: article

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.

Source: International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering

DOI: 10.11591/ijece.v10i5.pp4569-4580

Authors: Dian Sa'adillah Maylawati, Tedi Priatna, Hamdan Sugilar, Muhammad Ali Ramdhani

Institutions: Universiti Teknikal Malaysia Melaka, Sunan Gunung Djati State Islamic University Bandung

Language: English

Topic: Technology Adoption and User Behaviour

Subfield: Information Systems and Management

Field: Decision Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W3034232295

FWCI: 5.702

Cites: 70

Cited by: 27

Related to: 10