Open AccessMOBILE SCANNER ADOPTION ANALYSIS BETWEEN EMPLOYMENT AND EDUCATIONAL BACKGROUND – AN ANALYSIS OF LOGISTIC REGRESSION
Author(s) -
Indra Surya Permana,
Taufik Hidayat,
Rahutomo Mahardiko
Publication year - 2021
Publication title -
teknokom : jurnal teknologi dan rekayasa sistem komputer/teknokom
Language(s) - English
Resource type - Journals
eISSN - 2686-3219
pISSN - 2621-8070
DOI - 10.31943/teknokom.v4i2.56
Subject(s) - scanner , logistic regression , computer science , regression analysis , mobile apps , mobile device , artificial intelligence , machine learning , world wide web
As of today, the mobile apps may be downloaded everywhere. The development of mobile apps depends on the type of the work. An increasing use of mobile app is scanner apps due to an easy use. This paper presents the regression analysis on employment and educational background of the mobile scanner app because this research used category in the questionnaire. The use of logistic regression is to prove that any different comparisons are detected between employment and educational background so that the use of mobile scanner can be optimally used. The results show that educational background and employment have vital roles for mobile scanner adoption. This study also proves that previous researches on mobile scanner adoption were true for UTAUT model and comparison analysis.