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JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Article . 2025 . Peer-reviewed
License: CC BY SA
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Apriori Algorithm Analysis to Determine Purchasing Patterns at Beleven Farma Pharmacy

Authors: Fara Lufiah; Dwi Rosa Indah; Mgs Afriyan Firdaus;

Apriori Algorithm Analysis to Determine Purchasing Patterns at Beleven Farma Pharmacy

Abstract

Beleven Farma Pharmacy is a place that provides medicines and other health products such as supplements, vitamins and also various health tests. As a newly established pharmacy, no innovations have been made to improve sales strategies. Analysis of purchasing patterns can produce information that helps pharmacies in determining product bundling recommendations as well as determining product layout. This research applies the a priori algorithm method and uses rapidminer tools to identify drug purchasing patterns from transaction data at the Beleven Farma pharmacy. The Knowledge discovery in database (KDD) method is used as a reference in the data processing process. Based on tests carried out by the author, the resulting rules are that if you buy hemaviton you will buy vice with 4% support and 91% confidence and if you buy amoxicillin you will buy paracetamol with 4% support and 64% confidence. Thus, the resulting information can be used to support decision making in determining marketing strategies so as to increase sales at pharmacies.

Keywords

purchasing patterns, apriori algorithm, Electronic computers. Computer science, product bundling, QA75.5-76.95, transaction data analysis, knowledge discovery in database (kdd)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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