MOBILE SCANNER ADOPTION ANALYSIS BETWEEN EMPLOYMENT AND EDUCATIONAL BACKGROUND – AN ANALYSIS OF LOGISTIC REGRESSION

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Indra Surya Permana
Taufik Hidayat
Rahutomo Mahardiko

Abstract

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.

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Author Biographies

Indra Surya Permana, Universitas Nahdlatul Ulama Cirebon

Currently works at the Management, Universitas Nahdlatul Ulama Cirebon. Indra Surya does research in Algebra, Statistics and Marketing. Their current project is 'Islamic economics and the strategic issues that exist within it relate to the problems of Islamic economics and its solutions'.

Taufik Hidayat, Universitas Wiralodra

Currently, he is working as lecturer at Department of Computer Engineering, Universitas Wiralodra and doing some researches in IT Value, Blockchain and Internet of Things.

Rahutomo Mahardiko, Platinumetrix Pte. Ltd

Professional with some serious research on IT Value, Telecommunications, Start-up, Pandemic Covid-19, Electric Vehicle, Real Industry, Networking, Cloud Computing, Adoption Analysis, Statistical and Mathematical Analysis, Virtual Machine.

How to Cite
Permana, I. S. ., Hidayat, T., & Mahardiko, R. (2021). MOBILE SCANNER ADOPTION ANALYSIS BETWEEN EMPLOYMENT AND EDUCATIONAL BACKGROUND – AN ANALYSIS OF LOGISTIC REGRESSION. TEKNOKOM, 4(2), 37–42. https://doi.org/10.31943/teknokom.v4i2.56

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