Please use this identifier to cite or link to this item: http://dspace2020.uniten.edu.my:8080/handle/123456789/21185
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dc.contributor.authorSaipol H.F.S.en_US
dc.contributor.authorShamsuddin N.T.en_US
dc.contributor.authorCob Z.C.en_US
dc.contributor.authorGhani N.en_US
dc.contributor.authorDrus S.M.en_US
dc.date.accessioned2021-09-03T02:54:21Z-
dc.date.available2021-09-03T02:54:21Z-
dc.date.issued2019-
dc.identifier.urihttp://dspace2020.uniten.edu.my:8080/handle/123456789/21185-
dc.description.abstractThe purpose of this study is to investigate significant factors that influenced duration of solving financial institutions’ customer complaint. Using raw customer complaint dataset from Consumer Financial Protection Bureau (CFPB) website, it was found that many of sub-categories are not well organized. Thus, it is important to proceed with data cleaning and data preparation steps before any analysis been performed. In this study, Artificial Neural Network (ANN) had been chosen since it can deal with non-linear relationship by using sigmoid function. Further to this, it was found that Product, Company response and Issues are the significant factors that are more likely to be solved more than one day. The use of this analysis can be particularly beneficial for related financial party that might need to assist their customer in future. © BEIESP.en_US
dc.language.isoenen_US
dc.titleExamination of significant factors influencing response time of customer complaint based on analytics methoden_US
dc.typearticleen_US
item.cerifentitytypePublications-
item.languageiso639-1en-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextopen-
item.openairetypearticle-
Appears in Collections:UNITEN Ebook and Article
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