Abstract
In the world of international trade, export and import activities are very important activities especially for countries that have an open economy, such as our country, Indonesia. Where export is the activity of sending goods from abroad, while import is the activity of importing goods from abroad into the country. In Indonesia alone many companies are engaged in imports. As an importer company many obstacles are experienced, one of which is the accumulation of goods in the warehouse which causes losses for the company. This happens because of an imbalance between imported goods and market demand. Because of these problems, a method is needed to find out which products have the most sales and how the product is related to one another, one of the algorithms in the data mining algorithm is a priori algorithm. Apriori algorithms include types of association rules in data mining. One of the stages of association analysis that attracts many researchers to produce efficient algorithms is analysis of high frequency patterns (frequent pattern mining). The importance of an association can be known by two benchmarks, namely: support and confidence. Support (supporting value) is the percentage of the combination of these items in the database, while confidence (certainty value) is the strength of the relationship between items in the association rules. Apriori algorithms can help to develop an inventory strategy in order to facilitate marketing.
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