Penerapan Data Mining Menggunakan Algoritma Apriori Untuk Persediaan Stok Obat Pada Apotek Safa
DOI:
https://doi.org/10.33998/jms.2024.4.2.1753Keywords:
Data Mining; Algoritma Apriori; Asosiasi; Apotek; Stok ObatAbstract
Pharmacies as a health service facility need to prioritize the interests of the community and are obliged to provide, store and deliver pharmaceutical supplies that are of good quality and guaranteed. Safa Pharmacy, Jambi City, sells various kinds of health medicines such as chemical medicines, herbal medicines, and others. Apart from that, there is also a pharmacy that provides drug consultations and medical check-up services. The problem that currently occurs at the Safa Pharmacy is the lack of adequate drug supplies, namely that the sales of drugs that consumers or the public want are often absent or run out, resulting in consumers moving from one pharmacy to another. This causes slow service to consumers and reduces sales levels in pharmacies. By knowing drug purchasing patterns, we can provide information about consumer habits in purchasing drugs so that we can increase the supply of appropriate drugs. This can be done by utilizing drug sales data at the Safa Pharmacy using the a priori algorithm data mining technique. The final result was found from the highest support value and confidence value, namely, if you buy Wound Medicine, you will buy Wound Cleanser with support of 12% and confidence of 89%. If you buy Wound Cleaner, you will buy Wound Medicine with 12% support and 82% confidence. If you buy Flu Medicine, you will buy Cough Medicine with 9% support and 68% confidence. If you buy fever medicine, you will buy vitamins with 13% support and 60% confidence. If you buy Vitamins, you will buy Fever Medicine with 13% support and 60% confidence.
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References
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