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Implementasi data Mining Algoritma Apriori pada Sistem Persediaan Alat-alat Kesehatan

Extracting data or an effort to retrieve valuable knowladge and information in a large database is called data mining or Knowledge Discovery in Database or usually shortened as KDD . One of the most popular algorithm in data mining technic is Apriori Algorithm, while the discovery of “relational combination pattertn among itemset used Assosiation Rules”. Data mining has been implemented into the various fields like : business or trade, education and telecommunication. In bussiness for instance, the implementation result of data mining use ‘algorithm Apriori
which can give a hand to help the Businessmen make decision on supplies. For example, the necessity of supplies system in a drugstore as one of the mecical stuff supplier, and to determine which product as the priority should be supplied to anticipate out of stock of supplies availability in the store, as the results will also affect to the consumer service and daily income. Medical tools are essential unit should be supplied and being and essential
factor which will impact to the consumer trust to a hospital or another medical service. That is why the availability of medical tools in drugstores is completely needed to support the succes of distribution to the consumers, so the activity of medical service to consumers run thoroughly.
In this case, data mining is seen as able to buildt intelligent business environment as solution for competing increated compitition among the drugstores in future.

Keywords : Data Mining, Association Rules, Apriori Algorithm, Medical tools.

Statement of Responsibility
Author(s) Hoga Saragih - Personal Name
Kennedi - Personal Name
Bobby Reza - Personal Name
Edition Vol.I No.I, Oktober 2013
Call Number Karil -018
Subject(s) Data mining
Aturan Asosiasi
Algoritma Apriori
Alat-alat Kesehatan
Language Indonesia
Publisher STIMIK ERESHA
Publishing Year 2013
Specific Detail Info Majalah Ilmiah Informasi dan Teknologi Ilmiah (INTI), Vol.I No.I, Oktober 2013
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