Please use this identifier to cite or link to this item: http://ir.unikl.edu.my/jspui/handle/123456789/18896
metadata.conference.dc.title: Estimating the unemployment rate using least square and conjugate gradient methods
metadata.conference.dc.contributor.*: Nur Syarafina Mohamed
Mustafa Mamat
Mohd Rivaie
Nur Hamizah Abdul Ghani
Norhaslinda Zull
Syazni Syoid
(UniKL MITEC)
metadata.conference.dc.subject: Conjugate gradient method
Least square method
Unconstrained optimization
Workforce
metadata.conference.dc.date.issued: 8-May-2018
metadata.conference.dc.relation.ispartofseries: 7 (2.15) (2018) 94-97;
metadata.conference.dc.description.abstract: Unemployment rate is one of the major issues among Malaysian citizens. The unemployment rate indicates the percentage of the total workforce who are actively seeking employment and currently unemployed. In this paper, a data of unemployment rate of a state in Malaysia from year 2000 until 2015 is collected. The statistics data is extracted by Labour Force Survey Malaysia (LFSM) which was conducted monthly by using household approach targeted to working ages between 15 to 64 years old. An estimation data for year 2016 can be forecasted by using discrete least square method of numerical analysis and conjugate gradient method in unconstrained optimization. These methods have been chosen based on its simplicity and accuracy. The calculations are based on linear and quadratic models for each the method together with their errors. Results showed that the conjugate gradient method is comparable with the least square method.
metadata.conference.dc.identifier.uri: http://ir.unikl.edu.my/jspui/handle/123456789/18896
Appears in Collections:Journal Articles

Files in This Item:
File Description SizeFormat 
Estimating the unemployment rate using least square and conjugate gradient methods.pdf258.19 kBAdobe PDFView/Open


Items in UniKL IR are protected by copyright, with all rights reserved, unless otherwise indicated.