Association Rule Mining using Apriori algorithm for work-related beliefs of Generation X and Generation Y

Market-Basket Analysis is a process to analyze the habits of buyers to find the relationship between different items in their market basket. The discovery of these relationships can help the merchant to develop a sales strategy by considering the items frequently purchased together by customers. In this article, the data mining with market basket analysis method is implemented, for work-related beliefs of Generation X and Generation Y. The data testing is conducted from collection of questionnaire. There are 20 questions in our questionnaire. The data for frequent questions performed by Apriori algorithm to get the relation that often appear in the database. The questions are generated association rules after decoding. One frequent question can generate association rules and find the confidence. The test results show, the application can generate the information what kind of work-related beliefs are frequently bought in the same Generation according to the Association Rules criteria. Results from the mining process show a correlation between the data (association rules) including the support and confidence that can be analyzed. This information will give additional consideration for work-related beliefs of Generation X and Generation Y to make further decision.