Using factor analysis and regression analysis to develop mathematic modeling to support online application implementation in transportation business

• Published in: Journal of physics. Conference series Vol. 1538; no. 1; pp. 12042 - 12047
• Main Authors: Sardjono, W, Selviyanti, E, Perdana, W G
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.05.2020
• Subjects: Customer satisfaction; Dependent variables; Factor analysis; Independent variables; Mathematical models; Operational problems; Public transportation; Regression analysis; Transportation services; Variables
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1538/1/012042

Factor analysis is used to reduce data or summarize, from the old variable which is widely changed to a few new variables called factors, and still contains most of the information contained in the original variable. While regression analysis studies the relationship between one or more variables/independent variables (X) with one dependent variable (Y).The purpose of this paper is to describe how the factor analysis method can be used to provide solutions to operational problems such as problems with public transportation services with online applications, for this reason the research was conducted in identifying what factors influence the quality of online applications, and henceforth can be used in building mathematical models that can explain practical applications and predictions in the future. This research is explained in a quantitative descriptive form using exploratory factor analysis and regression analysis methods to process primary data and build models. The conclusion of this study is that there are 22 indicators and three factors that determine the quality of the application. The three factors produced are system and information factors, user impact factors, and promotion factors. These three factors can henceforth become a model in determining customer satisfaction as an end user of public transportation with an online application.