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dc.contributor.authorYip, Kai Leung
dc.date.accessioned2013-01-21T20:32:50Z
dc.date.available2013-01-21T20:32:50Z
dc.date.issued2012en_NZ
dc.identifier.urihttps://hdl.handle.net/10652/2036
dc.description.abstractWith the aid of open-sourced database and software libraries, we developed a data mining software prototype for SME business intelligent budgeting planning. The experiment demonstrates the existence of the change pattern of financial variables for a certain SME industry group. A budget inaccuracy alarm system is developed. The system classifies a budget whether viable or inviable. As a result, SME businesses or non-profit organisations can make better decisions by improving forward looking financial analysis. This allows them to immediately develop contingency measures, revise the policy and get the business back on the right track. This has been a long-desired function needed by a business or a bank.en_NZ
dc.language.isoenen_NZ
dc.subjectbudget change pattern tecognitionen_NZ
dc.subjectbudgetingen_NZ
dc.subjectbusiness planningen_NZ
dc.subjectdata miningen_NZ
dc.subjectfinancial forecasten_NZ
dc.subjectfinancial ratioen_NZ
dc.subjectfinancial variableen_NZ
dc.subjectgovernment budgeten_NZ
dc.subjectintelligent budgetingen_NZ
dc.subjectmachine learningen_NZ
dc.subjectsmall and medium-sized enterprises (SMEs)en_NZ
dc.subjectsmall businessesen_NZ
dc.titleDetermining the accuracy of budgets : a machine learning application for budget change pattern recognitionen_NZ
dc.typeMasters Thesisen_NZ
thesis.degree.nameMaster of Computingen_NZ
thesis.degree.levelMastersen_NZ
thesis.degree.grantorUnitec Institute of Technologyen_NZ
dc.subject.marsden080109 Pattern Recognition and Data Miningen_NZ
dc.identifier.bibliographicCitationYip, K. L. (2012). Determining the accuracy of budgets : a machine learning application for budget change pattern recognition. (Unpublished document submitted in partial fulfilment of the requirements for the degree of Master of Computing). Unitec Institute of Technology. Retrieved from https://hdl.handle.net/10652/2036en
unitec.pages78en_NZ
dc.contributor.affiliationUnitec Institute of Technologyen_NZ
unitec.advisor.principalPang, Paul
unitec.advisor.associatedZhao, Xiaohui
unitec.institution.studyareaComputing


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