Application of Data Mining Algorithm to Recipient of Motorcycle Installment
Keywords:motorcycle financing credit, CRISP DM, data mining, algorithms C4.5, Confusion Matrix, ROC
The study was conducted in the subsidiaries that provide services of finance related to the purchase of a motorcycle on credit. At the time of applying, consumers enter their personal data. Based on the personal data, it will be known whether the consumer credit data is approved or rejected. From 224 consumer data obtained, it is known that the number of consumers whose applications are approved is 87% or about 217 consumers and consumers whose application is rejected is 16% or as much as 6 consumers. Acceptance of motorcycle financing on credit by using the method of applying the algorithm through CRIS-P DM is the industry standard in the processing of data mining. The algorithm used in the decision making is the algorithm C4.5. The results obtained previously, the level of accuracy is measured with the Confusion Matrix and Receiver Operating characteristic (ROC). Evaluation of the Confusion Matrix is intended to seek the value of accuracy, precision value, and the value of recall data. While the Receiver Operating Characteristic (ROC) is used to find data tables and comparison Area Under Curve (AUC).
Darudiato, S., Santoso, S.W. & Wiguna, S. (2010). Business Intelligence: Konsep dan Metode. Jurnal CommIT, 4(1), 63 – 67.
Gorunescu, F. (2011). Data Mining: Concepts, Models, and Techniques. Verlag Berlin Heidelberg: Springer.
Han, J., Kamber, M. (2006). Data Mining Concept and Tehniques. New York: Morgan Kauffman
Kusrini, Luthfi, E. T. (2009). Algoritma Data Mining. Yogyakarta: Andi Publishing.
Larose, D. T. (2005). Discovering Knowledge in Data. New Jersey: John Willey & Sons Inc.
Sulianta, F., Juju, D. (2010). Data Mining Meramalkan Bisnis Perusahaan. Jakarta: PT. Elex Media Komputindo.
Sumathi, S., Sivanandam, S. N. (2006). Introduction to Data Mining and its Applications. New York: Springer-Verlag Berlin Heidelberg.
Authors who publish with this journal agree to the following terms:
a. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License - Share Alike that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
b. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
c. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
All articles published Open Access will be immediately and permanently free for everyone to read and download. We are continuously working with our author communities to select the best choice of license options, currently being defined for this journal as follows: