Determining the accuracy of budgets : a machine learning application for budget change pattern recognition
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Authors
Yip, Kai Leung
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Degree
Master of Computing
Grantor
Unitec Institute of Technology
Date
2012
Supervisors
Pang, Paul
Zhao, Xiaohui
Zhao, Xiaohui
Type
Masters Thesis
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
budget change pattern tecognition
budgeting
business planning
data mining
financial forecast
financial ratio
financial variable
government budget
intelligent budgeting
machine learning
small and medium-sized enterprises (SMEs)
small businesses
budgeting
business planning
data mining
financial forecast
financial ratio
financial variable
government budget
intelligent budgeting
machine learning
small and medium-sized enterprises (SMEs)
small businesses
ANZSRC Field of Research Code (2020)
Citation
Yip, 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 (Unpublished document submitted in partial fulfilment of the requirements for the degree of Master of Computing).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/10652/2036
Abstract
With 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.
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