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Discount is a sales strategy that lowers the price offered to buyers in the hope of increasing sales profits. However, when offering these discounts, stores often don't think about how discounted products can attract customers, so a support system is needed that can respond to the right and appropriate discounts. This support system with data mining techniques using apriori algorithm. This apriori method can search for several products that are often purchased simultaneously, therefore when juxtaposed with this study the effectiveness of the recommendations will be very good. Not only that, if it is added with a combination of recommendations with discounts, it will make customers interested to buying the product. The expected result of this research is to obtain a new sales strategy by making recommendations on items that will be used as discount packages.

ABSTRACT The rapid development of technology has a very large effect in various fields. One of them is in the field of buying and selling business, which is getting higher and higher competition between business actors. One of the strategies to increase sales is to implement a recommendation for goods, but from the various categories of goods in the store, there are products that are not in demand by customers, so that if left alone, the products that are not in demand will not sell well and will make the accumulation of goods in the store, in addition to that with the many categories, it makes some customers confused to choose products that suit their wishes buyer. Therefore, the author conducts an assessment first by conducting a literature study, which finally the purpose of this study is to make it easier for users and business owners to recommend goods in the store and determine the desired product by implementing a recommendation system on the Rameiki Mart Store website which is taken from the amount of data, this is also beneficial for store owners because the existence of this recommendation system can help as a means of product promotion , as well as in recommendations for the purchase of goods. In this study, the researcher created a recommendation system using the a priori algorithm method.

In a business , the ability to process data is very necessary, information obtained from a business can provide benefits in  an effective and efficient business strategy, but with the development of online business strategy information, some users,  in business furniture products are confused choosing product according to the wishes of the buyer Therefore, research is made with the aim of making it easier for users, especially in the field of furniture product business to determine the desired product by implementing a recommendation system on the furniture store website which is taken from the amount of data, this data can be in the form of databases. this is also beneficial for shop owners because with this recommendation system it can help as a means of promoting products that are not selling well. the recommendation system uses the a priori algorithm method with data mining techniques, namely association rules.