Asia Pacific University Library catalogue


DATA MODELLING APPROACH TO IDENTIFY POTENTIAL OWNERSHIP OF UNKNOWN ASSESTS IN AN IT ORGANIZATION / (Record no. 383008)

000 -LEADER
fixed length control field 02392nam a2200241 4500
003 - CONTROL NUMBER IDENTIFIER
control field APU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230626115526.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200224b2019 ||||| |||| 00| 0 eng d
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number PM-31-60
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name PREMAWATY A/P MAHINDRA KUMAR (TP028419)
9 (RLIN) 45390
245 10 - TITLE STATEMENT
Title DATA MODELLING APPROACH TO IDENTIFY POTENTIAL OWNERSHIP OF UNKNOWN ASSESTS IN AN IT ORGANIZATION /
Statement of responsibility, etc PREMAWATY A/P MAHINDRA KUMAR.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Kuala Lumpur :
Name of publisher, distributor, etc Asia Pacific University,
Date of publication, distribution, etc 2019.
300 ## - PHYSICAL DESCRIPTION
Extent 69 pages :
Other physical details illustrations ;
Dimensions 30 cm.
502 ## - DISSERTATION NOTE
Dissertation note A 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 ## - SUMMARY, ETC.
Summary, etc The 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 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Database management
General subdivision Software.
9 (RLIN) 45391
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data structures (Computer science)
9 (RLIN) 45392
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Interpretation, Statistical.
9 (RLIN) 45393
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Management information systems.
9 (RLIN) 45394
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Prof Dr. R. Logeswaran
Relator term Supervisor.
-- 47624
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://cas.apiit.edu.my/cas/login?service=https://library.apu.edu.my/apres/
Link text Available in APres
Public note - Requires login to view full text.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Masters Theses
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Use restrictions Not for loan Collection code Home library Current library Shelving location Date acquired Full call number Barcode Date last seen Copy number Koha item type Public note
Not Withdrawn Available   Not Damaged Restricted access Not for loan Masters Theses APU Library APU Library Reference Collection 24/02/2020 PM-31-60 00017675 24/02/2020 1 Reference Available in APres