Open AccessPENERAPAN DATA MINING DENGAN ASSOCIATION RULES UNTUK MELIHAT HUBUNGAN TERTANGGUNG, PEMILIHAN PRODUK DAN PERILAKU NASABAH (Studi Kasus: PT. Prudential Life Assurance)
Author(s) -
Awan Setiawan,
Erwin Yulianto
Publication year - 2019
Publication title -
jurnal accounting information system
Language(s) - English
Resource type - Journals
ISSN - 2621-7279
DOI - 10.32627/aims.v2i1.63
Subject(s) - association rule learning , apriori algorithm , competition (biology) , life insurance , business , actuarial science , asset (computer security) , computer science , data mining , computer security , ecology , biology
The world of insurance business that is full of competition makes the perpetrators must always think about breakthrough strategies that can guarantee the continuity of their insurance business. One of the main assets owned by insurance companies is business data in an extraordinary amount.Data mining is a new technology that is very useful to help insurance companies find very important information from business data as the main asset they have. Data mining can predict trends and traits of business behavior that are very useful to support important decision making. Automated analysis carried out by data mining exceeds that carried out by traditional support systems. Apriori and FP-Growth are the most famous algorithms for finding high frequency patterns, these algorithms are part of the Rule Association used in this study.