Penerapan Data Mining dengan Algoritma Apriori Pada Data Penjualan Obat Untuk Mengetahui Pola Pembelian Obat Pada Apotek Di Kota Nabire

Abstract

There are quite a lot of pharmacies in the city of Nabire where they sell various kinds of health medicines such as chemical, herbal, and other drugs. In addition, there are also pharmacies that serve drug consultations, doctor services, health checks, and so on. The problem that occurs in pharmacies today is the lack of adequate drug supplies, namely where often the sale of drugs desired by consumers or the public does not exist or runs out, resulting in these consumers moving from one pharmacy to another. This makes service slow to consumers and reduces the level of sales in pharmacies. Knowing drug purchasing patterns can provide information about consumer habits in buying drugs so that it can provide insight into service improvement, proper drug supply, and can understand disease trends in a region. This can be done by utilizing drug sales data in pharmacies using data mining techniques, a priori algorithm association methods. The final result found 4 association rules with a minimum value of support of 30% and a minimum value of confidence of 50% with calculations using Microsof excel and using the Ripedminer application If you buy Mefenamic and Grantussive Acid, you will buy Bodrex with support 34.21%, confident 58.81%, lift ratio of 1.00. If you buy Mefenamic Acid and Dexa, then buy Bodrex with a support value of 36.09%, a confident value of 62.04%, a lift ratio of 1.05. If you buy Mefenamic Acid and Dexa, then buy Paracetamol with a support value of 31.42%, a confident value of 68.85%, a lift ratio of 1.43. If you buy Mefenamic Acid and Dexa, then buy Amoxilin with a support value of 31.01%, a confident value of 68.04%, a lift ratio of 1.44.