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Analisa Data Penjualan Pada Apotek Ritonga Farma Menggunakan Data Mining Apriori Lestari, Putri Anggraini; Nasution, Marnis; Harahap, Syaiful Zuhri
Jurnal Informatika Vol 12, No 2 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i2.5651

Abstract

A pharmacy is a place or business that is specifically dedicated to providing medicines and other health products to the public. This place is also known as a drugstore or drug store in some countries.  Pharmacies provide medicines both prescribed by doctors and over-the-counter (over-the-counter), to help patients cope with health problems they are experiencing.Some pharmacies also offer additional services such as blood pressure checks, vaccinations, simple health checks, and health counseling to the public.  In applying a priori methods to pharmacy, a deep understanding of data structure and proper product classification is needed to overcome this problem. By knowing the pattern of frequent purchases, pharmacies can place items that are often purchased together close together on shelves or strategic locations. This can increase the convenience of buyers and speed up the purchase process. A priori methods are techniques in data mining that are used to find hidden patterns or associations in large datasets.  A priori methods look for relationships between items in a dataset that often appear together.  The main principle of the a priori method is that if an item-set appears frequently together, then it is likely that the item-set will also appear frequently together in other transactions.