Presented at the 4th International Symposium on Innovative Approaches in Engineering and Natural Sciences (ISAS WINTER-2019 (ENS)), Samsun, Turkey, Nov 22, 2019

SETSCI Conference Proceedings, 2019, 9, Page (s): 58-60 , https://doi.org/10.36287/setsci.4.6.022

Published Date: 22 December 2019    | 1160     9

There are many factors that affect students' motivation to learn. Number of friends, friendship satisfaction and communication skills are some of the important factors. In scientific studies, friendship and peer rejection have unique effects on academic achievement. Besides, it was emphasized that if friendship relations were positive, it was effective on emotional development. However, there are very limited number of studies examining the friendship relationships of university students by using data mining techniques. Data mining is widely used in many different disciplines today. In its most basic definition, data mining is the extraction of meaningful information from a data set. With the increase of computer the capacity and power, studies in the field of data science have become easier. In this study, the association between friendship, age, gender, department and academic achievement was analyzed with the frequently used association algorithm in data mining. Survey method was used to collect data. Rapidminer software, which is popular in the world, was used for data analysis. As a result of the study, it was determined that friendship relations should be taken into consideration in academic success. It is seen that communication quality is effective in school success as well as in social life. Meanwhile, it has been determined that data mining methods can be used effectively in academic achievement of students.

Keywords - Friendship, student, data mining, algorithm, communication

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