Open AccessIMPLEMENTASI DATA MINING PADA PENJUALAN PRODUK DI CV CAHAYA SETYA MENGGUNAKAN ALGORITMA FP-GROWTH
Author(s) -
Wahyu Nur Setyo,
S.Sn. Sakundria Wardhana
Publication year - 2019
Publication title -
petir/petir (jakarta. online)
Language(s) - English
Resource type - Journals
eISSN - 2655-5018
pISSN - 1978-9262
DOI - 10.33322/petir.v12i1.416
Subject(s) - database transaction , computer science , association rule learning , transaction data , data mining , volume (thermodynamics) , database , data warehouse , set (abstract data type) , physics , quantum mechanics , programming language
At this time the growth of data occurs rapidly and rapidly along with the use of computer systems in various transactions. But this increasingly large volume of data has no meaning if it is not processed into a knowledge where this is done by data mining. Association rule or what is known as market based analysis is one type of data mining implementation. This study aims to find patterns of transaction data in the CV Cahaya Setya retail industry by using an Frequent Pattern Growth algorithm or also known as FP-Growth algorithm. FP-Growth aims to find all the set items that can be retrieved (often found) from the transaction database as efficiently as possible. The results of this study show that the pattern on the database of consumer transactions at CV Cahaya Setya retail industry is can be found using the FP-Growth algorithm then implementing it in the application.