The Mapping and Identification Model of It Technopreneurships Student Potential Using Data Mining and Artificial Intelligence
Year: 2025
Type: article
Abstract: The Information Technology (IT) Technopreneurships are growing very rapidly in line with technological increasing. This study aims to produce a model for mapping and identifying of student potential in IT (information technology) technopreneurships using intelligent computing. This mapping is based on the existence of 4 areas of IT technopreneurship, namely Software Application developer, Data Analyst, Computer System & Network engineer and Multinedia& Graphics Developer. The indicators used are: interesting, entrepreneurial values, learning styles (Solitary, Logical, Aural, Social, Verbal, visual and Physical) and multiple intelligences (Visual Spatial, Logical Mathematics, Body Kinesthetics, Naturalist, Musical, Linguistics, Interpersonal and Intrapersonal. This study used research and development and action research approach methods. The development of an intelligent computing system used the prototype method. The resulted of internal testing of running well models with cyclometic complexity was lower. The novel model that has been produced is a mapping based on students personal cognitive characteristics for IT technopreneurship based on intelligent computing. User acceptance Test resulted 96%, Expertise judgment Test (Computing / IT) yields 98% and Expertise Judgment Test (Entrepreneurships / Technopreneurships) yields 95%. The result of model validation of 20 IT technopreneurships was precise 85%. The resulted of the implementation of the model resulted in 60 students of Software Application developer, 65 students of Data Analysis, 56 students of Computer Systems & Network engineers, 50 students of Multinedia& Graphics Developer and 24 students not suitable to become IT technopreneurs.
Author: Journal of Theoretical and Applied Information Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7083428433
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