Analysis of the Application of Transaction Data with Association Techniques using the Apriori Algorithm in Pharmacy

  • Wahyudi Nasutioni Universitas Dinamika Bangsa
  • Dodo Zaenal Abidin Universitas Dinamika Bangsa
  • Errissya Rasywir Universitas Dinamika Bangsa
Keywords: Analysis, Data Mining, Pharmacy, Association, Transaction

Abstract

The development of information technology influences the rapid growth in the amount of data collected and stored in large t. Dimas Pharmacy, located at Jl. Segara Kec. Nipah Panjang is one of the public health services that sells various medicines, medical devices, and so on. This study is expected to provide positive benefits for owners of Dimas Nipah Panjang Pharmacy in Providing information about the pattern of medicine purchases made by consumers and Facilitating pharmacy owners to know the available medicine supplies in the warehouse so as not to experience emptiness when needed. Problem Formulation, Literature Study, Data Collection, Calculation and Analysis of Associations with Priori Algorithms, Results Evaluation and Analysis and Report Making. Based on the results of interviews and observations that have been made, the authors obtain data from the Dimas Pharmacy sales transaction. Data held ± 1000 sales transaction data for the period of May and June. But the author only entered 216 sales transactions in May and 141 sales transactions in June. After knowing the method of data selection, the authors conducted data selection by taking 6 items of significant data specifications in certain contexts, namely Anti Serotonin / Allergy, Antacid / Ulcer, Antibiotics, Antipyretics, Inflammation, Hypertension Each of these items had different brands. From these results it can be explained that the sales transaction of the Dimas Pharmacy in May and June generates or generates relationships between shopping product items. With the calculation of the Apriori Association Algorithm, a Market Basket Analysis relationship was found between Medicinal Pronicy and Dexa items. With the Rule "IF Buy Pronicy, THEN Buy Dexa". The rule is generated from the highest support and confident values of the overall support and confident items. The highest support value is 0.15 and the highest confident value is 0.5 ".

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Published
2023-09-30
How to Cite
Nasutioni, W., Abidin, D. Z., & Rasywir, E. (2023). Analysis of the Application of Transaction Data with Association Techniques using the Apriori Algorithm in Pharmacy. Journal of Applied Business and Technology, 4(3), 271-281. https://doi.org/10.35145/jabt.v4i3.141