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SALES FORECASTING OF PHARMACEUTICAL `PRODUCTS USING ASSOCIATION RULE MINING (ARM) METHOD Riska Dhenabayu; Ryan Ahmad Syah Putra
JOSAR (Journal of Students Academic Research) Vol 2 No 2: September 2017
Publisher : Universitas Islam Balitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/josar.v2i02.630

Abstract

This forecasting application can be applied to the pharmaceutical industry including the PPNI Wlingi pharmacy, which sells a variety of over-the-counter and prescription drugs and medical devices. The purchase of over-the-counter drugs is recorded daily. This, if left unchecked, will caused an accumulate sales data without any utilization of these data. Instead, the data can be used to determine the inventory turn over of goods so that it is useful in future sales strategies. One method that can be used is the Association Rule Mining (ARM) method which implement association rules. Association rule can be used to predict patterns of interrelationship between items that are often purchased by customers. The result will make it easier for companies to make the decision to increase or decrease the stock so that the inventory turn over will be shortened and reduce the risk of innefficient accumulation of goods.