Please use this identifier to cite or link to this item: https://repositori.uma.ac.id/handle/123456789/31002
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dc.contributor.authorElveny, Marischa-
dc.contributor.authorSyah, Rahmad B. Y.-
dc.contributor.authorNasution, Mahyuddin K. M.-
dc.date.accessioned2026-08-18T02:17:08Z-
dc.date.available2026-08-18T02:17:08Z-
dc.date.issued2023-06-22-
dc.identifier.urihttps://repositori.uma.ac.id/handle/123456789/31002-
dc.description8 Pagesen_US
dc.description.abstractWhen a business concentrates too much on acquiring new clients rather than retaining old ones, mistakes are sometimes made. Each customer has a different value. Customer lifetime value (CLV) is a metric used to assess long-term customer value. Customer value is a key concern in any commercial endeavor. When there are variations in customer behavior, CLV forecasts the value of total customer income when the data distribution is not normal, and outliers are present. Robust M-estimation, a maximum likelihood type estimator, is used in this study to enhance CLV data. Through the minimization of the regression parameter from the residual value, robust M-estimation eliminates data outliers in customer metric data. With an accuracy of 94.15%, R-square is used to gauge model performance. This research shows that CLV optimization can be used as a marketing and sales strategy by companies.en_US
dc.language.isoenen_US
dc.publisherIJ-AIen_US
dc.relation.ispartofseriesISSN;2252-8938-
dc.subjectBusiness intelligenten_US
dc.subjectCustomer lifetime valueen_US
dc.subjectM-estimationen_US
dc.subjectOptimizingen_US
dc.subjectRobusten_US
dc.titleAn Boosting Business Intelligent to Customer Lifetime Value with Robust M-Estimationen_US
dc.title.alternativeAn Boosting Business Intelligent to Customer Lifetime Value with Robust M-Estimationen_US
dc.typeArticleen_US
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