An Application on Technology Addiction with C4.5 Classification Algorithm

Abstract

The increment of the usagethe technological applications and tools, has led to an increase towards technology regarding for communication in the way of individuals' desire.With the development of technologies that facilitate our lives, rapid increases in individuals' use of technological tools have been observed.This has led to the fact that data mining and technology dependence concepts, which are expressed as the process of obtaining confidential information, are hidden in the large scale data in the digital environment and have become more involved in scientific studies. This study was carried out to determine the technology dependence of the students who continue their education in vocational and technical education based on C4.5 decision tree algorithm which is one of the data mining classification methods.In the questionnaire, the students were asked whether there is any positive or negative relationship between technology addiction and course success and demographic characteristics.Demographic information in the data set shows the characteristics and the question shows the class.The decision tree model of 411 observations in the data set was created using R programming language.The effect of demographic information such as gender, profession, number of siblings, date of birth on the class was determined according to the model made with C4.5 decision tree algorithm.As a result of the research, the most important feature that determines the answers is gender and the accuracy rate of the model is determined as 84.42%.