Title page for etd-0610118-235652


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URN etd-0610118-235652
Author Yi-chun Lin
Author's Email Address No Public.
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Department Finance
Year 2017
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Applying Decision Tree to Optimize Online Trading Audit Strategy.
Date of Defense 2018-05-31
Page Count 56
Keyword
  • Online Trading Audit Strategy
  • Classification and Regression Tree (CART)
  • Decision Tree
  • Abstract Development of the internet technology is advancing, and the proportion of online shopping greatly increased. According to the declaration of business tax data by online trading business entity, we find that the quantity of online trading business entity increasing from 2007, but the amount of business tax is not growth in the same proportion. In other words, the evasion of business tax is far more serious than we know.
    The purpose of this research is to optimize online trading audit strategy. We utilize Classification and Regression Tree (CART) algorithm to construct a decision tree from taxation database of Ministry of Finance, in order to observe the characteristic of the online trading business entity who has been punished for tax evasion, and furthermore, the characteristic of those who are more prone to be punished, and to improve the dilemma of audit we met in the past, make auditor more useful and lift the efficiency of audit.
    Advisory Committee
  • yan shing, Chen - chair
  • Shih sian, Jhang - co-chair
  • Feng tse, Tsai - co-chair
  • Chia fen, Tsai - advisor
  • Files
  • etd-0610118-235652.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2018-07-11

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