000			02392nam a2200241 4500
003			APU
005			20230626115526.0
008			200224b2019 ||||| |||| 00| 0 eng d
050			_aPM-31-60
100	0		_aPREMAWATY A/P MAHINDRA KUMAR (TP028419) _945390
245	1	0	_aDATA MODELLING APPROACH TO IDENTIFY POTENTIAL OWNERSHIP OF UNKNOWN ASSESTS IN AN IT ORGANIZATION / _cPREMAWATY A/P MAHINDRA KUMAR.
260			_aKuala Lumpur : _bAsia Pacific University, _c2019.
300			_a69 pages : _billustrations ; _c30 cm.
502			_aA thesis submitted in fulfillment of the requirement for the award of the degree of Master of Science in Data Science and Business Analytics (UCMP1610DSBA)
520			_aThe purpose of this study is to identify potential unknown asset owners through data modelling approach based on analysis of asset and vulnerability management data. Research studies are discussed to understand the current assets and vulnerability management and approach to identify unknown assets within an organization. Knowledge discovery in database methodology is applied throughout this study to obtain desired outcomes. Based on the research design implementation of the data modelling and the result obtained are further discussed. Decision tree and random forest model has been developed in this study to obtained model accuracy based on current organization practice to identify unknown assets. The accuracy of both model developed are compare whereby the shortcoming of the less accurate model were highlighted. It was identified that the random forest model displayed better accuracy than the decision tree modelling. Validation of the results were examined with real-life organization scenarios. Furthermore, area of improvements to maintain the data integrity and data quality within the organization is suggested. Finally, the study explains future works that could be considered to obtain more prominent results.
650		0	_aDatabase management _xSoftware. _945391
650		0	_aData structures (Computer science) _945392
650		0	_aData Interpretation, Statistical. _945393
650		0	_aManagement information systems. _945394
700			_aProf Dr. R. Logeswaran _eSupervisor. _947624
856	4	0	_uhttps://cas.apiit.edu.my/cas/login?service=https://library.apu.edu.my/apres/ _yAvailable in APres _z- Requires login to view full text.
942			_2lcc _cMasters Theses
999			_c383008 _d383008