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 |