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A Data Mining Analysis of ERP System using Frequent Pattern Growth Algorithm

by Ayman G. Fayoumi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 26
Year of Publication: 2018
Authors: Ayman G. Fayoumi
10.5120/ijca2018918154

Ayman G. Fayoumi . A Data Mining Analysis of ERP System using Frequent Pattern Growth Algorithm. International Journal of Computer Applications. 182, 26 ( Nov 2018), 30-35. DOI=10.5120/ijca2018918154

@article{ 10.5120/ijca2018918154,
author = { Ayman G. Fayoumi },
title = { A Data Mining Analysis of ERP System using Frequent Pattern Growth Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2018 },
volume = { 182 },
number = { 26 },
month = { Nov },
year = { 2018 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number26/30142-2018918154/ },
doi = { 10.5120/ijca2018918154 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:12:34.275650+05:30
%A Ayman G. Fayoumi
%T A Data Mining Analysis of ERP System using Frequent Pattern Growth Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 26
%P 30-35
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Enterprise Resource Planning (ERP) system has become an inevitable necessity for organizations to automate their business processes in an integrated environment. Literatures on ERP systems suggested many dimensions to enhance the working capabilities of ERP system based on different perspectives. This paper aims to understand and analyze the effective use of datasets generated through this system, where multiple entities working together using shared database. Currently, the main challenge for ERP managers is how to deal with this generated data and makes best use of it. To address this challenge, this research presents a model that to understand and analyze ERP data, using data mining approach. Furthermore, model validation on a medium size organization that is selected as a case study is performed to validate the implementation and use of proposed framework. A data set extracted from a selected organization to perform association-mining using Frequent Pattern (FP) growth algorithm, which can generate and predict rules using experienced data. The validation outcome illustrates the usefulness of the model. In addition, results also indicate that, the analytical approach on ERP database creates constructive implications over business and it helps the organization realizing the more benefits of ERP system. Ultimately, the proposed model and its implementation can be suitable for ERP users and managers to generate rules and suggestions for the future queries in an anticipated manner.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining ERP database FP-Growth Algorithm Rules Generation

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