Implementation of data mining with Apriori techniques to determine the pattern of purchasing of agricultural equipment (Case Study: XYZ Store). Issue 1 (June 2021)

• Record Type: Journal Article
• Authors: Supriyono, ; Ferine, Kiki Farida; Puspitasari, Diana; Rulinawaty, ; Timotius, Elkana
• Is Part Of: Journal of physics. Volume 1933:Issue 1(2021)
• Publication Date: 2021-06
• Subjects: Analysis -- Data Mining -- Rule Association -- Apriori -- Agriculture; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1933/1/012029
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The aim of this research is to take advantage of data mining techniques using the Apriori sales data algorithm for agricultural equipment. This is due to the fact that the high potential agricultural sector in Indonesia has obstacles to the use of technology. Research was conducted in the district of Simalungun in a shop selling agricultural needs. Sales activities in the store continue and generate more and more data. In order to be of use to the resulting data, it is necessary to process these data with a certain algorithm that provides great benefits, in particular by maximizing the sales profits of agricultural products. Apriori Algorithm is one of the methods of data mining, the activities of which include data collection and the use of old data with the aim of finding regularities, patterns or relationships in data collection. The output of the algorithm can help future decision-makers, where one of the advantages is the rearrangement of the product layout, such as the most frequently sold products being assembled so that they are easily visible to consumers and can properly prepare stock items for the store.