Implementasi Algoritma Apriori Untuk Menentukan Stok Obat

Abstract

The supply of drugs in a pharmacy is very important to maintain the fulfillment of consumer needs based on a doctor's prescription. Problems arise due to limitations on the expiry date of each drug, this needs to be overcome so that there is no buildup of drug stocks at the pharmacy so that it causes losses because there are types of drugs that have expired in sufficient quantities, therefore we need data mining that can determine which pattern of drug type works best, using a priori algorithm. The association method is needed to see the correlation between a number of attributes for example if a consumer buys drug A then he will buy drug B as well. A priori analysis to determine the minimum conditions for support and confidence. The conclusion of this research is that if you buy amlodipine 5 mg, you will buy sanmol, this is obtained from 33.33% support and 66.66% confidence, if you buy 500 mg amoxan, you will buy sanmol with a support value of 41.66% and confidence 71, 42% and if you buy sanmol, you will buy amoxan 500 mg with a support value of 41.66% and confidence 62.50%.

Keywords

• data mining
• a priori algorithm, drug inventory