Forecasting ATM transactions

dc.authorid0000-0002-0556-7482en_US
dc.contributor.authorCilacı Tombuş, Ayşe
dc.contributor.authorAlbayrak, Erdal
dc.date.accessioned2024-07-12T20:48:03Z
dc.date.available2024-07-12T20:48:03Z
dc.date.issued2019en_US
dc.departmentFakülteler, İnsan ve Toplum Bilimleri Fakültesi, Matematik Bölümüen_US
dc.description.abstractInstalling the ATMs to the right and effective points, which are the only channel providing cash transactions among Digital Channels, is the key point in terms of cost decrease and ease of customer access in the banking sector. The main purpose of this study is supporting installation of a new ATM decision both outdoor and indoor (in the Shopping Centers) by using data mining and forecasting techniques. We have used 1,115 existing ATM parks for Outdoor ATM transactions forecasting, and 195 points for Shopping Center ATMs Transaction Number Estimation. We have used data mining techniques because of the huge amounts of data. Multivariate regression analysis has been performed according to district / neighborhood population, other bank ATM clustering, number of customers in neighborhood detail, neighborhood saving and neighborhood household income, shopping center size, number of stores and parking capacity data. In this study, R-based R Studio program has been used for all classification and estimation methods.en_US
dc.identifier.citationCilacı Tombuş, A. ve Albayrak, E. (2019). Forecasting ATM transactions. International Conference of Mathematical Sciences (ICMS 2019). s. 186.en_US
dc.identifier.endpage187en_US
dc.identifier.isbn978-605-2124-29-1
dc.identifier.startpage186en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12415/2088
dc.language.isoenen_US
dc.publisherMaltepe Üniversitesien_US
dc.relation.ispartofInternational Conference of Mathematical Sciences (ICMS 2019)en_US
dc.relation.publicationcategoryUluslararası Konferans Öğesi - Başka Kurum Yazarıen_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.snmzKY01450
dc.subjectMulti-regressionen_US
dc.subjectData miningen_US
dc.subjectForecastingen_US
dc.subjectRen_US
dc.titleForecasting ATM transactionsen_US
dc.typeArticle
dspace.entity.typePublication

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