Association Pattern Discovery of Import Export Items in Ethiopia

Mezgeb Manaye Gebru

Abstract


This paper examines the application of data mining to detect association pattern of customs administration data with market price and currency rate exchange in Ethiopia. The association rule method of data mining is used in this paper to generate the interesting pattern from the data. This study was done to identify the relationships between attributes of custom data and market price to clearly understand the nature of import-export items in Ethiopia. The results of the experiments carried out using association rules revealed that the technique of data mining is applicable to generate knowledge from import and export items in custom administration. Algorithms such as Apriori, Tertius, PredictiveApriori and FliteredApriori were used to generate the associations. One of the resulting associations indicates that there is a strong link between market price and textiles imported. The implication of this research finding is that it clearly identified the association of import-export items with the market price and the effects of those items on the market price and currency rate in Ethiopia.


Keywords


Data mining; Association rule; Weka; Association pattern; Apriori; Tertius; PredictiveApriori; FliteredApriori; Algorithm.

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