Pemodelan Loyalitas Konsumen Susu Pertumbuhan dalam Mengikuti Program Rewards Menggunakan Metode Random Forest dan Neural Network

Authors

  • Ayunda Pratiwi Department of Statistics, IPB
  • Khairil Anwar Notodiputro Department of Statistics, IPB
  • Hari Wijayanto Department of Statistics, IPB

DOI:

https://doi.org/10.29244/xplore.v2i2.104

Keywords:

AUC, backpropagation, CART, churn, classification.

Abstract

Business competition in Indonesia has been becoming more competitive. This is the reason for companies to create a strategy in maintaining their customers through of loyalty program. However, on one of the rewards programs in nutrition companies, 37.62% of registered members have left the program or commonly known as churn. The classification model of customer loyalty is built to anticipate this, based on their profiles and activities in the program during the prediction period. The classification model is built for the two largest brands with random forest and neural network methods. These two methods are evaluated and compared based on the ROC (Relative Operating Characteristics) curve by considering the area under curve (AUC) value. The performance of these two methods are not significantly different, but neural network method yields greater AUC value, both in modeling of brand A and brand B.

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Published

2018-08-31

How to Cite

Pratiwi, A., Notodiputro, K. A., & Wijayanto, H. (2018). Pemodelan Loyalitas Konsumen Susu Pertumbuhan dalam Mengikuti Program Rewards Menggunakan Metode Random Forest dan Neural Network. Xplore: Journal of Statistics, 2(2), 41–48. https://doi.org/10.29244/xplore.v2i2.104