Record Details

USE OF DATA MINING TECHNIQUES IN ADVANCE DECISION MAKING PROCESSES IN A LOCAL FIRM

European Journal of Business and Economics

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Field Value
 
Title USE OF DATA MINING TECHNIQUES IN ADVANCE DECISION MAKING PROCESSES IN A LOCAL FIRM
 
Creator Doğan, Onur; Dokuz Eylül University, İzmir
Aşan, Hakan ; Dokuz Eylül University, İzmir
Ayç, Ejder; Dokuz Eylül University, İzmir
 
Subject Decision making, Data mining, Decision tree algorithms
C80, D83
 
Description In today’s competitive world, organizations need to make the right decisions to prolong their existence. Using non-scientific methods and making emotional decisions gave way to the use of scientific methods in the decision making process in this competitive area. Within this scope, many decision support models are still being developed in order to assist the decision makers and owners of organizations. It is easy to collect massive amount of data for organizations, but generally the problem is using this data to achieve economic advances. There is a critical need for specialization and automation to transform the data into the knowledge in big data sets. Data mining techniques are capable of providing description, estimation, prediction, classification, clustering, and association. Recently, many data mining techniques have been developed in order to find hidden patterns and relations in big data sets. It is important to obtain new correlations, patterns, and trends, which are understandable and useful to the decision makers. There have been many researches and applications focusing on different data mining techniques and methodologies.In this study, we aim to obtain understandable and applicable results from a large volume of record set that belong to a firm, which is active in the meat processing industry, by using data mining techniques. In the application part, firstly, data cleaning and data integration, which are the first steps of data mining process, are performed on the data in the database. With the aid of data cleaning and data integration, the data set was obtained, which is suitable for data mining. Then, various association rule algorithms were applied to this data set. This analysis revealed that finding unexplored patterns in the set of data would be beneficial for the decision makers of the firm. Finally, many association rules are obtained, which are useful for decision makers of the local firm. 
 
Publisher CBU, o.p.s.
 
Contributor —
 
Date 2015-12-19
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://ojs.journals.cz/index.php/EJBE/article/view/682
10.12955/ejbe.v10i2.682
 
Source European Journal of Business and Economics; Vol 10, No 2 (2015)
1804-9699
10.12955/ejbe.v10i2
 
Language eng
 
Relation https://ojs.journals.cz/index.php/EJBE/article/view/682/628
 
Rights Copyright (c) 2015 Onur Doğan, Hakan  Aşan, Ejder Ayç
https://creativecommons.org/licenses/by/3.0/