Almira Van Fadhila, . (2023) PENERAPAN DATA MINING UNTUK POLA REKOMENDASI PEMBELIAN OBAT DENGAN MENGGUNAKAN ALGORITMA APRIORI PADA PT. SEHAT ANUGERAH PHARMINDO. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Apotek is a company engaged in the sale of medicine. Where this company every day must meet the needs of consumers both personal and other pharmacies and are required to take the right decisions in determining sales strategies. In order to do this, companies need concrete sources of information for further analysis. At pharmacies, especially at PT. Sehat Anugerah Pharmindo, there are several problems that often arise regarding sales where this pharmacy has difficulty getting information on product sales per period so that there is difficulty in getting information about medicine that are sought after or medicine purchased at the same time, causing non-optimal sales when one the product that are commonly purchased concurrently are not available. The availability of abundant data is not used as much as possible and there is no decision support system and method that can be used to design a business strategy to increase sales. The use of the Apriori Algorithm method should be a solution for this. By implementing data mining using a priori algorithms to find out what types or brands of medicine are in demand in the future or future strategies. This research produces a system that can help analyze and predict sales products according to the needs of pharmacies.
Item Type: | Thesis (Skripsi) |
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Additional Information: | [No.Panggil : 1910511019] [Pembimbing : Anita Muliawati ] [Penguji 1 : Didit Widiyanto ] [Penguji 2 : Bayu Hananto ] |
Uncontrolled Keywords: | apriori algorithm, system, pharmacy, data mining, prediction. |
Subjects: | Q Science > Q Science (General) |
Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
Depositing User: | Almira Van Fadhila |
Date Deposited: | 02 Aug 2023 08:57 |
Last Modified: | 02 Aug 2023 08:57 |
URI: | http://repository.upnvj.ac.id/id/eprint/25976 |
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