Customer Loyalty Classification With Random Forest Algorithm

Anggi Puspita Sari(1*), Astrid Noviriandini(2), Sifa Fauziah(3),

(1) Universitas Bina Sarana Informatika, Indonesia
(2) Universitas Bina Sarana Informatika, Indonesia
(3) Universitas Bina Sarana Informatika, Indonesia
(*) Corresponding Author

Abstract


Customer loyalty is very important for the survival of the company. Because with customers who have customer loyalty, they will make purchases regularly. Customer loyalty needs to be maintained to increase profits. The method is to classify loyal customers with non-loyal ones, in order to retain loyal customers and set strategies for non-loyal customers. The method used is classification with random forest with cleaning stages that can clean data from noise or empty data or data that does not match, selection that can select some data to be processed for classification, transformation that can change data into two or three formats, classification with random forest with split validation using testing data and training data and with rapidminer software. Evaluation by checking the results of the classification with random forest in the form of accuracy, precision, recall, and AUC. The results of the classification show from the accuracy table that the prediction of loyal and true loyal customers is 129 more than the prediction of not loyal and true not loyal customers which is 32. The accuracy result is 96.41% which shows that the data is really accurate with very high results. The recall result is 98.47%, while the precision result is 96.99%.

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References


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DOI: https://doi.org/10.30645/ijistech.v9i1.393

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