Please use this identifier to cite or link to this item: http://41.63.8.17:80/jspui/handle/123456789/158
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dc.contributor.authorKunda, Douglas-
dc.contributor.authorChihana, Sipiwe-
dc.date.accessioned2023-08-09T14:15:22Z-
dc.date.available2023-08-09T14:15:22Z-
dc.date.issued2017-01-02-
dc.identifier.citationIEEE Styleen_US
dc.identifier.urihttp://41.63.8.17:80/jspui/handle/123456789/158-
dc.descriptionArticleen_US
dc.description.abstractThe growth of information Technology has spawned large amount of databases and huge data in numerous areas. The research in database and information technology has given rise to an approach to store and manipulate this data for further decision making. In this paper certain data mining techniques were adopted to analyze the data that shows relevance with desired attributes. Regression technique was adopted to help us find out the influence of agriculture, Service and Manufacturing on the performance of gross domestic products (GDP). Trend and time series technique was applied to the data to help us find out what trend of GDP with respect to service , agriculture and manufacturing sector for the past decade has been. Finally Correlation was also used to help us analyze the relationship among the variable (service, agriculture and manufacturing sector). From the three techniques analyzed, service value added variable was the most prominent variable which showed the strong influence on GDP growth rate.en_US
dc.description.sponsorshipMulungushi Universityen_US
dc.language.isoen_USen_US
dc.publisherDatabase Systems Journal vol. VIII, no. 2/2017en_US
dc.subjectGDP, Regression, Time-series/trends analysis, Correlation, Data mining, Predictionsen_US
dc.titleAnalysis of value added service on GDP Growth Rate using Data Mining Techniquesen_US
dc.typeArticleen_US
Appears in Collections:Research Papers and Journal Articles

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