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PENERAPAN ASSOCIATION RULE UNTUK MENGANALISA DATA KONSUMEN KEPEMILIKAN RUMAH SUBSIDI

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dc.contributor.author Sinaga, Jordiansyah Simto
dc.date.accessioned 2023-05-04T03:44:54Z
dc.date.available 2023-05-04T03:44:54Z
dc.date.issued 2023-01
dc.identifier.citation Perpustakaan en_US
dc.identifier.other Elfitra
dc.identifier.uri https://repository.unri.ac.id/handle/123456789/10947
dc.description.abstract Increasing population growth and increasingly limited land for housing needs has led to high public interest in housing loans so that they can pay installments every month. But problems that often occur are errors in determining the credit period and the number of installments paid each month causing credit arrears. This causes difficulties for developers in recommending services that are in accordance with the consumer's economy at PT. Semangat Jaya Sentosa enthusiasm for processing data manually. So to overcome this problem, companies need recommendations in the form of strategies obtained from consumer data at PT. Semangat Jaya Sentosa. This study aims to obtain Association Rules from consumer data and information on housing loans. The results of the Association Rules will form strategic recommendations for the developer. The attributes used are gender, status, occupation, district/city, credit period, and income. This study carried out 6 stages in obtaining Association Rules namely literature study, data collection, data selection, data cleaning, implementation of a priori algorithms, and interpretation. This study uses the Python programming language to find Association Rules from consumer housing loan data sets and through join and prune processes. This study uses consumer data for the period from January to December 2021 as many as 1,514 data with a minimum Support value of 30% and a minimum Confidance of 83% so as to produce a pattern of 18 rules so that the highest value for the combination of 3 itemset is Pekanbaru, Lowerclient, 20 has a Support value of 0.4557 = 45.57 % and Confidance value 1 = 100%. The results of the interpretation of the rules concluded, the developer can provide recommendations regarding the appropriate credit period for consumers with income below 3 million rupiah from the Pekanbaru city area, which is 20 years. The results of the Association Rules are then formed to recommend the best strategy for the developer and are expected to be able to overcome the problem of housing loans at PT. Semangat Jaya Sentosa. en_US
dc.description.provenance Submitted by wahyu sari yeni (ayoe32@ymail.com) on 2023-05-04T03:44:54Z No. of bitstreams: 1 Jordiansyah Simto Sinaga_compressed.pdf: 231530 bytes, checksum: 9269b7d709974c1809dbb25f47362d94 (MD5) en
dc.description.provenance Made available in DSpace on 2023-05-04T03:44:54Z (GMT). No. of bitstreams: 1 Jordiansyah Simto Sinaga_compressed.pdf: 231530 bytes, checksum: 9269b7d709974c1809dbb25f47362d94 (MD5) Previous issue date: 2023-01 en
dc.description.sponsorship Fakultas Matematika dan Ilmu Pengetahuan Alam en_US
dc.language.iso en en_US
dc.publisher Elfitra en_US
dc.subject Apriori en_US
dc.subject Algorithm Association Rule Method en_US
dc.subject Consumer data patterns en_US
dc.subject Data mining en_US
dc.subject Home Ownership Loans en_US
dc.title PENERAPAN ASSOCIATION RULE UNTUK MENGANALISA DATA KONSUMEN KEPEMILIKAN RUMAH SUBSIDI en_US
dc.type Article en_US
dc.contributor.supervisor Alfirman, Alfirman


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