FP-Growth Algoritması Kullanılarak Tüketiciler ve Mobilya Kullanım Süresi Arasındaki İlişkilerin Belirlenmesi

Abstract

Furniture is widely used by people in all cultures at different times for various purposes in daily life. Furniture and human interaction is an important issue that needs to be examined in many ways. In order to protect the health of consumers and to fully understand their purchasing behavior, information about the life span of furniture is needed. In this study, demographic information of consumers and usage times for different furniture were determined by survey method. Using the Frequent Pattern (FP)-Growth algorithm from the data obtained, the relationship between the usage time of different furniture and the consumers was found. As a result of the study, it was determined that the strongest association was between those who spent the shortest time on their furniture to eat, being overweight and male. The proposed method based on data mining shows that the relationships between consumers and the usage time for different furniture can be determined effectively and successfully. Data science can offer decision makers new perspectives to understand consumer behavior. However, there is a need for new studies based on data analysis to increase quality in the furniture industry.

Veri Madenciliğine Dayalı Olarak Çalışanların Örgütsel Bağlılık Düzeyinin Belirlenmesi: İstanbul ve Kocaeli Örneği

“…Günümüzde, işletmeler veri madenciliğinin değerini giderek daha iyi anlamakta ve sürekli olarak yeni alanlarda uygulamalarını genişletmektedir. Veri madenciliği yöntemleri, literatürde farklı disiplinlerde yaygın bir şekilde kullanılmıştır ve bu teknikler, çeşitli karmaşık problemlerin çözümünde önemli bir araç olarak kabul edilmiştir (Sözen et al, 2022;Sözen et al, 2021;Bardak et al, 2021;Karayılmazlar et al, 2019;.…”