The classification of workforce requirement planning for service oriented operations

dc.authorid0000-0003-1250-5949en_US
dc.contributor.authorÖzpınar, Alper
dc.contributor.authorSerengil, Şefik İlgin
dc.date.accessioned2019-08-20T08:43:16Z
dc.date.available2019-08-20T08:43:16Z
dc.date.issued2016en_US
dc.departmentFakülteler, Mühendislik Fakültesien_US
dc.description.abstractIn today’s world of competitive international economy sectors, service industry or service sector oriented businesses, the key point is to maximize the efficiency and sustainability of the business directly related with optimal planning of the workload and distributing them among the employees. Helpdesks and operation centers are one of the fastest developing service area of this sector. This paper compares the machine learning algorithms that can be used for the classification of workforce requirements for a bank operation center which provides support to reduce operational workload of bank branches. Classification of the workload based on the quantity of Money Order and EFT operations within time zones aids in the management of workforce teams and distribution of jobs between team members.en_US
dc.identifier.endpage158en_US
dc.identifier.issue12en_US
dc.identifier.startpage152en_US
dc.identifier.urihttps://hdl.handle.net/11467/2880
dc.identifier.volume4en_US
dc.language.isoenen_US
dc.publisherAuricle Technologiesen_US
dc.relation.ispartofInternational Journal on Recent and Innovation Trends in Computing and Communicationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBank Operationsen_US
dc.subjectWorkforce Planningen_US
dc.subjectClassificationen_US
dc.subjectMachine Learningen_US
dc.subjectANNen_US
dc.subjectBayesian Networksen_US
dc.subjectSMOen_US
dc.subjectSVMen_US
dc.titleThe classification of workforce requirement planning for service oriented operationsen_US
dc.typeArticleen_US

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