The discovery of association rules of book usage with data mining techniques: A case study of Panyananthaphikkhu Chonprathan Medical Center Library, Srinakharinwirot
Keywords:
Association rules, Book usage, Data mining, FP-Growth AlgorithmAbstract
The purpose of this study was to analyze the association rules for book usage. Panyananthaphikkhu Chonprathan Medical Center Library, Srinakharinwirot University. Using an experimental approach. The research employed data mining techniques and the FP-Growth algorithm, following the standard process for data mining called CRISP-DM (Cross-Industry Standard Process for Data Mining). The CRISP-DM consists of six steps: 1) Business Understanding, 2) Data Understanding, 3) Data Preparation, 4) Model Building, 5) Model Evaluation, and 6) Model Deployment. The data analysis revealed that there are 11 book items that are likely to be borrowed together, with a confidence level greater than or equal to 50%.
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