Asosiasi Tempat Wisata Dengan Kata Kunci Di Malang Raya Dengan Metode Association Rule Mining Menggunakan Algoritme FP-Growth - Fardan Ainul Yaqiin; Fitra Abdurrachman Bachtiar; Indriati Indriati (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Tourist attraction in Indonesia is growing rapidly. This growth made tourists hard to choose a destination. FP-Growth is an algorithm that uses frequent patterns in forming associations. FP-Growth can be used in the search for tourist attractions associations with its keywords, where these associations can later be used by tourists for reference in choosing destinations, also can be used by managers to improve their services. This study uses commentary data as a set of transactions as input for the formation of associations. In the resulting rule withdrawal, only suffixes of tourist attractions is taken so that the rule produced is the association of tourist attractions with its keywords. Testing is done to determine the effect of minimum support and minimum confidence on the number of rules formed and the average value of lift ratio. The conclusion of this study is the FP-Growth algorithm could be implemented in the formation of association of tourist attractions with keywords. The average lift ratio value of the association formed is 2.77, which means that the association is considered beneficial. In addition, the results of the associations obtained will later be used by managers of tourist attractions to improve their services.