Using Data Mining Techniques to Analyze Student's Preferences for Smartphones

A Comparative Study between iOS and Android Users in Higher Technical Institutes in Libya

Abstract

The intention of this particular study is to evaluate student smartphone preferences through data mining techniques on survey data collected from higher technical institute students in Libya. Special emphasis is placed on performing a comparative study with iOS and Android users to ascertain their purchasing decision drivers. An association rules mining approach using the FP-Growth algorithm was utilized to uncover user behavioral patterns and correlations among demographic features of users. The findings underscored the importance of the price, camera quality, security, and peer's advice influencing students’ decisions, showing significant differences between the two user groups. This study has provided an analysis that can be used in marketing and product development planning focused to the students' needs.