The library is a source of information and a place of learning. Each book lending information is stored by the library so as to produce large data lending books. Big data if not utilized will create problems in the future. In this study, researchers will utilize a priori algorithms and Tanagra software to group library book borrowing data at Ahmad Dahlan ITB based on trends that occur together in library visit activities. In the process of borrowing books, of course the raw data will be processed by dividing it into different pieces of data. Among the lending data tables processed are general lending tables, 2-itemset candidate tables, lending tabular tables, support value tables, confidence value tables. From the results of this study it can be seen what books are often borrowed together with a minimum support of 5% and 10% confidence one of which is Taxation and Taxation Accounting with a minimum support of 7.30% confidence 62.79%. And can be used as a reference for ITB Ahmad Dahlan in the procurement and placement of library book layout.
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