Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/22642
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dc.contributor.authorTrivodaliev, Kireen_US
dc.contributor.authorAleksandar Petkovski,en_US
dc.contributor.authorRisteska Stojkoska, Biljanaen_US
dc.contributor.authorKalajdziski, Slobodanen_US
dc.date.accessioned2022-08-26T08:14:23Z-
dc.date.available2022-08-26T08:14:23Z-
dc.date.issued2016-11-22-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/22642-
dc.description.abstractCustomer churn is one of the main problems in the telecommunications industry. Several studies have shown that attracting new customers is much more expensive than retaining existing ones. Therefore, companies are focusing on developing accurate and reliable predictive models to identify potential customers that will churn in the near future. The aim of this paper is investigating the main reasons for churn in telecommunication sector in Macedonia. The proposed methodology for analysis of churn prediction covers several phases: understanding the business; selection, analysis and data processing; implementing various algorithms for classification; evaluation of the classifiers and choosing the best one for prediction. The obtained results for the data from a telecommunication company in Macedonia, should be of great value for management and marketing departments of other telecommunication companies in the country and wider.en_US
dc.publisherIEEEen_US
dc.subjectchurn prediction, data mining, decision trees, KNN, logistic regression, naïve Bayesen_US
dc.titleAnalysis of churn prediction: a case study on telecommunication services in Macedoniaen_US
dc.typeProceeding articleen_US
dc.relation.conference24th Telecommunications Forum (TELFOR)en_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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