PENERAPAN DATA MINING BERBASIS ALGORITMA FP-GROWTH UNTUK MENENTUKAN STRATEGI PROMOSI BERBASIS BUNDLING

Rizka Ardiansyah, Wirdayanti Wirdayanti, Yuri Yudhaswana, Nanda Idris

Abstract

The level of competition in the business world requires every marketer to be able to carry out their marketing activities more effectively and efficiently. These marketing activities require a basic marketing concept in accordance with the interests of marketers and the needs and desires of customers/consumers. The purpose of this research is to increase the effectiveness of promotional strategies with the bundling method through the implementation of a computerized system to ensure the stability of the flow of goods without having to burden warehouse costs and mapping promotional strategies through managing consumer shopping data. This research uses the association method with the Fp-Growth algorithm. The achievement of this research is that by capitalizing on transaction data for one year, the lift ratio test results show the validity level of the association rules obtained at a confidence value of 10%-15%. This is because the level of randomness of the data is still too high. The greater the confidance value, of course, the more effective the output rule will be.

Keywords

Data Mining; Fp-Growth; Association; Marketing; Bundling;

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References

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