Dhea Laksmi Prianto, . (2021) IMPLEMENTASI CHURN PREDICTION DI INDUSTRI TELEKOMUNIKASI DENGAN METODE LOGISTIC REGRESSION DAN CORRELATION-BASED FEATURE SELECTION. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Telecommunication industry became one of the industry that is becoming more competitive and is growing interest in churn prediction for customer. Churn prediction is about how to detect customer who have tendency to leave the service. This prediction is one of the company’s effort to retain customers in Customer Relationship Management (CRM). Several authors suggest that logistic regression method has good modelling and performance results to be applied to predictive data. Dataset is taken from one of the United States’ telecommunication company named Orange which available on Kaggle website then proceed to analyze the performance of churn prediction using data mining with correlation-based feature selection forward selection and machine learning logistic regression algorithm.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 1710511025] [Pembimbing 1: Iin Ernawati] {Pembimbing 2: Nurul Chamidah] [Penguji 1: Ermatita] [Penguji 2: Bayu Hananto] |
| Uncontrolled Keywords: | churn prediction, customer relationship management (CRM), logistic regression, data mining, correlation-based feature selection, forward selection, machine learning |
| Subjects: | T Technology > T Technology (General) T Technology > T Technology (General) > T201 Patents. Trademarks |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Dhea Laksmi Prianto |
| Date Deposited: | 06 Apr 2022 08:21 |
| Last Modified: | 06 Apr 2022 08:21 |
| URI: | http://repository.upnvj.ac.id/id/eprint/16862 |
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