Penerapan Data Mining dalam Analisis Pola Pembelian Minuman dan Makanan di Kantin SMAN 4 Langsa Menggunakan Algoritma FP-Growth
Dublin Core
Title
Penerapan Data Mining dalam Analisis Pola Pembelian Minuman dan Makanan di Kantin SMAN 4 Langsa Menggunakan Algoritma FP-Growth
Subject
Canteen, Products, FP-Growth, FP-Tree, Rules
Description
Every school in Indonesia have a canteen. The canteen provided by schools to
meet the needs of students. The diversity of students patterns in buying drinks
and foods in canteen also varies. to find out how the pattern of these students in
buying food in the canteen is to use one of the data mining methods, namely
FP-Growth. FP-Growth is an improvement of apriori algorithm. FP-Growth
builds FP-Tree. The databases have to be scanned twice in FP-Tree to determine
frequent itemset, so making it more effective than apriori. The data used in this
research is transaction data to buy foods and drinks in the canteen. This research
used Rapidminer software for association rules. The results of this research have
two forms, the rules that are calculated manually and the rules through
Rapidminer. Then the results will be used for canteen manager to study the
patterns of students in buying drinks and foods in the canteen.
meet the needs of students. The diversity of students patterns in buying drinks
and foods in canteen also varies. to find out how the pattern of these students in
buying food in the canteen is to use one of the data mining methods, namely
FP-Growth. FP-Growth is an improvement of apriori algorithm. FP-Growth
builds FP-Tree. The databases have to be scanned twice in FP-Tree to determine
frequent itemset, so making it more effective than apriori. The data used in this
research is transaction data to buy foods and drinks in the canteen. This research
used Rapidminer software for association rules. The results of this research have
two forms, the rules that are calculated manually and the rules through
Rapidminer. Then the results will be used for canteen manager to study the
patterns of students in buying drinks and foods in the canteen.
Creator
Rizky Fitria Haya, Desy Ramadani
Publisher
Perpustakaan Horizon Karawang
Date
2019
Contributor
Fajar Bagus W
Format
PDF
Language
Indonesia
Type
Text
Files
Collection
Citation
Rizky Fitria Haya, Desy Ramadani, “Penerapan Data Mining dalam Analisis Pola Pembelian Minuman dan Makanan di Kantin SMAN 4 Langsa Menggunakan Algoritma FP-Growth,” Repository Horizon University Indonesia, accessed November 21, 2024, https://repository.horizon.ac.id/items/show/3247.