HPAI Consumer Shopping Analysis using Apriori Algorithm Yulian Findawati, Sumarno, Yunianita Rachmawati, Ika Nur Hikmah
PT Herba Penawar Alwahida sells a variety of herbal products. The process of buying and selling transactions occur every day, resulting in a pile of datapretty much. However, so far the transaction data has only been used as material to make monthly reports without further use of data these, even though from these data information can be extracted to support marketing. To utilize existing transaction data, the authors make a website based data mining application. This application will be developed by method association (Association Rule) uses apriori algorithm. So that it can be seen the level of accuracy of this application. With the application of data mining, is expected to help the distributor to get information about which HPAI products are often purchased by consumers simultaneously, so as to improve the product marketing and maintaining process availability of stock of these products to remain.
Abstract
PT Herba Penawar Alwahida sells a variety of herbal products. The process of buying and selling transactions occur every day, resulting in a pile of datapretty much. However, so far the transaction data has only been used as material to make monthly reports without further use of data these, even though from these data information can be extracted to support marketing. To utilize existing transaction data, the authors make a website based data mining application. This application will be developed by method association (Association Rule) uses apriori algorithm. So that it can be seen the level of accuracy of this application. With the application of data mining, is expected to help the distributor to get information about which HPAI products are often purchased by consumers simultaneously, so as to improve the product marketing and maintaining process availability of stock of these products to remain.
