<![CDATA[Library is one _ source information and places study . Every information loan book saved by library so that generate loan data book in size big . Big data if not used _ will make problem in the future day .In study this , researcher will use technique for grouping loan data book library . based on emerging trend _ together in something activity visit library . In carry out the loan process book , of course only raw data will processed with share it into the different data fragments .For repair system manager library in study this with use method Algorithm a priori . Among the processed loan data tables is a loan table by general , 2-itemset candidate table, borrowing tabular table, support value table, confidence value table. For make this Data Mining process easier , researchers use Anaconda Navigator application , from the transaction data table loan 2016-2019 which became object study this .In testing algorithm a priori using Python and using available Jupiter apps in Anaconda. In testing writer convert the data into a .csv file format . Based on results testing and analysis from application algorithm a priori in pattern loan books in the library of our Education Foundation, then could drawn conclusion that Algorithm a priori could used for knowing book what only often _ appears in the loan process book , and found couple in loan book student Sandicta are (1-2 3600 seconds – pocong also pocong ) and (12-20 4R – Always With Me ) Keywords: Loan Patterns, Data Mining, Association Rules, Apriori Algorithm]]>
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