Walisongo Journal of Information Technology · 2019 · 34 citations · 0 references
ComputingBusiness AdministrationData MiningEducational Data MiningPromotion ManagementFrequent Pattern MiningPromotion StrategyAssociation Rule LearningAssociation Rule MiningPattern MiningPromotion PatternRule Mining
Effective promotion strategies are essential for organizations to reduce costs and achieve marketing goals. The study applied the Apriori data‑mining algorithm to university promotion data, examining variables such as school, region, and department to uncover association rules. The analysis yielded informative association patterns that can guide universities in designing promotion strategies to attract new students.
<p><em>Every company and organization that wants to survive needs to determine the effectiveness of the right promotion strategy. Determination of the right promotion strategy will be able to reduce the cost of promotion and achieve the right promotional goals. One way that can be done to determine the promotion strategy is to use data mining techniques. Data mining techniques used in this case are using the Apriori algorithm. A priori algorithm is one of the classic data mining algorithms. A priori algorithms are used so that computers can learn the rules of association, look for patterns of relationships between one or more items in a dataset. This study is conducted by observing several research variables that are often considered by universities in determining their promotion goals, namely school, region, and department. The results of this study are in the form of interesting patterns resulting from data mining which is important information to support the right promotion strategy in getting new students.</em></p>