Aplikasi Web Usage Mining Menggunakan Metode Association Rule Dengan Algoritma Fp-Growth Untuk Mengetahui Pola Browsing Pengunjung Website

Abstract

As a way to improve the promotion of institutions via the web, there is a need for a method to view browsing patterns of visitors on the site unilak.ac.id, thereby showing the user's interest in the links he visits. Data mining or knowledge discovery is a process of extracting valuable information by analyzing the existence of certain patterns or relationships. To find visitor patterns in the form of association rules is to use the association rule method. FP-Growth is an alternative algorithm that can be used to determine the most frequent set of data in a set of data. FP-Growth is applied to get a pattern of visitors, about what links are frequently visited and seen by visitors on the site unilak.ac.id. This pattern is used to help web administrators in developing the site unilak.ac.id by utilizing knowledge from the association pattern to regulate the layout / layout design of the categories available on the site unilak.ac.id. From the results of processing the dataset with FP-Growth algorithm and processing data processed using data mining software, namely Rapidminer 6.5. It was found that the minimum value of support was 1% and the minimum confidence value of 50% resulted in 124 rules of association.

Penerapan Algoritma FP-Growth untuk Menentukan Strategi Promosi Berdasarkan Waktu dan Pembelian Produk

“…Algoritma FP-Growth dianggap lebih bagus dari pada algoritma apriori karena algoritma FP-Growth memiliki konsep dalam membangun pohon [20]. Dengan memakai algoritma FP-Growth didapatkan pengetahuan yang baru berupa informasi tentang pola pembelian untuk meningkatkan strategi promosi [21]. Algoritma FP-Growth juga dapat menyimpan secara ringkas memori dalam database [22].…”