Work

Telecommunication Service Subscriber Churn Likelihood Prediction Analysis Using Diverse Machine Learning Model

Year: 2020

Type: conference-paper

Source: International Conference on Mechanical, Electronics, Computer, and Industrial Technology (MECnIT)

DOI: 10.1109/mecnit48290.2020.9166584

Authors: Ngurah Putu Oka H, Ajib Setyo Arifin

Institution: University of Indonesia

Language: English

Topic: Customer churn and segmentation

Subfield: Marketing

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: closed

OpenAlex ID: W3049670950

FWCI: 4.385

Cites: 8

Cited by: 9

Related to: 10