Bima Wahyu Utama
Universitas Jenderal Achmad Yani

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Implementasi Frequent Pattern Growth untuk Melihat Trend dari Penjualan Tisu di PT XYZ Bima Wahyu Utama; Tacbir Hendro Pudjiantoro
Prosiding SISFOTEK Vol 4 No 1 (2020): Vol 4 No 1 (2020): SISFOTEK 2020
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Prediction is a technology that learns from experience (data) to predict individual behavior in the future to encourage better decisions. Prediction is different from forecasting, forecasting makes aggregate predictions at the macroscopic level. Tissue is a practical cleaning tool for use and multifunctionality, so that tissue is commonly found and used by the public, tissue is used for travel equipment, complement the dining table, and cleaning tools stored in modern toilets. The sale of tissue, which sometimes cannot be fulfilled, makes some customers stop buying tissue from the company. The use of Frequent Pattern Growth algorithm or FP-Tree which is a development of apriori algorithm is one alternative algorithm to determine the set of data that often appears. The use of the Frequent Pattern Growth method for the case of tissue sales predictions gets fairly accurate results and can make it easier for related sections to see tissue demand trends in a country calculated based on tissue trends in the previous month.