PENERAPAN DATA MINING MARKET BASKET ANALYSIS TERHADAP POLA FREKUENSI KERANJANG BELANJA MENGGUNAKAN ALGORITMA FREQUENT PATTERN GROWTH (FP-GROWTH) DAN ECLAT

WIJAYA, KRISNA NATA and Malik, Reza Firsandaya and Nurmaini, Siti (2020) PENERAPAN DATA MINING MARKET BASKET ANALYSIS TERHADAP POLA FREKUENSI KERANJANG BELANJA MENGGUNAKAN ALGORITMA FREQUENT PATTERN GROWTH (FP-GROWTH) DAN ECLAT. Master thesis, Sriwijaya University.

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Abstract

Buying and selling transaction activities in minimarkets or shop owners must understand what consumers want in providing shopping comfort, especially the ease in selecting goods that are adjusted to the layout or placement of goods. The application of the data mining concept can help business owners or business people plan and make predictions of goods from sales patterns, applying association rules to transaction data will make it easier for owners to manage sales information and search for itemsets. Therefore, this study analyzes patterns of sales transaction data by applying the association method to data mining. Data is prepared by going through a data selection process, data cleaning and transformed into a form that can be processed by the system. Furthermore, the data is processed using the FP-Growth and ECLAT algorithms by comparing the results of the algorithm in the form of association rules that are formed and the processing time speed of each algorithm with a minimum support and confidence of 0,01% to determine the number of strong rules in tables and graphs as material. the decision maker indicated for the shopping basket frequency and the higher the support value, the fewer association items obtained, on the contrary the smaller the value of support, the more the resulting rules are formed.

Item Type:	Thesis (Master)
Uncontrolled Keywords:	Aturan Asosiasi, Algoritma FP-Growth, ECLAT
Subjects:	H Social Sciences > HF Commerce > HF5410-5417.5 Marketing. Distribution of products > HF5415.126.R38 Database marketing--Statistical methods. Data mining--Statistical methods. Big data--Statistical methods. T Technology > T Technology (General) > T58.6-58.62 Management information systems
Divisions:	09-Faculty of Computer Science > 55101-Informatics (S2)
Depositing User:	Users 8982 not found.
Date Deposited:	24 Nov 2020 06:59
Last Modified:	24 Nov 2020 06:59
URI:	http://repository.unsri.ac.id/id/eprint/37867

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