Membangun Model Prediksi Churn Pelanggan yang Akurat

Studi Kasus tentang TELCO Company

Authors

  • Andy Hermawan Universitas Indraprasta PGRI
  • Nila Rusiardi Jayanti Universitas Indraprasta PGRI Jakarta
  • Zia Tabaruk Universitas Bhayangkara Jakarta Raya
  • Faizal Lutfi Yoga Triadi Universitas Diponogoro
  • Aji Saputra Universitas Khairun
  • M.Rahmat Hidayat Syachrudin Purwadhika Digital Technology School Jakarta

DOI:

https://doi.org/10.61132/merkurius.v2i6.398

Keywords:

Customer churn, Churn prediction, Machine learning, Telecom industry, TELCO Company

Abstract

Customer churn prediction models have become an important tool in the telecommunications industry to reduce churn rates and improve customer retention. This research focuses on building an accurate customer churn prediction model using machine learning algorithms for TELCO Company. By applying diverse feature engineering techniques and prediction models such as RandomForestClassifier, DecisionTreeClassifier, and XGBoost, this study showcases a significant improvement in prediction accuracy compared to previously implemented rule-based methods. The findings of this research allow TELCO Company to identify high-risk customers more effectively and implement targeted retention strategies. Results show that the resulting model can identify customers at risk of churn more effectively, enabling more targeted retention actions..

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Published

2024-10-07

How to Cite

Andy Hermawan, Nila Rusiardi Jayanti, Zia Tabaruk, Faizal Lutfi Yoga Triadi, Aji Saputra, & M.Rahmat Hidayat Syachrudin. (2024). Membangun Model Prediksi Churn Pelanggan yang Akurat: Studi Kasus tentang TELCO Company. Merkurius : Jurnal Riset Sistem Informasi Dan Teknik Informatika, 2(6), 67–81. https://doi.org/10.61132/merkurius.v2i6.398

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