eprintid: 10705
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/07/05
datestamp: 2023-11-09 16:37:19
lastmod: 2023-11-09 16:37:19
status_changed: 2023-11-09 16:32:01
type: article
metadata_visibility: show
creators_name: Isa, N.H.M.
creators_name: Othman, M.
creators_name: Karim, S.A.A.
title: Multivariate matrix for fuzzy linear regression model to analyse the taxation in Malaysia
ispublished: pub
note: cited By 2
abstract: A multivariate matrix is proposed to find the best factor for fuzzy linear regression (FLR) with symmetric triangular fuzzy numbers (TFNs). The goal of this paper is to select the best factor influence tax revenue among four variables. Eighteen years' data of the variables from IndexMundi and World Bank Data. It is found that the model is successfully explained between independent variables and response variable. It is notices that (HR = 0.66) sixty-six percent of the variance of tax revenue is explained by Gross Domestic Product, Inflation, Unemployment and Merchandise Trade. The introduction of multivariate matrix for fuzzy linear regression in taxation is a first attempt to analyses the relationship the tax revenue with the independent variables. © 2018 Authors.
date: 2018
publisher: Science Publishing Corporation Inc
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059243449&doi=10.14419%2fijet.v7i4.33.23490&partnerID=40&md5=85b81b3bf10c38cd624ccac8d41818e1
id_number: 10.14419/ijet.v7i4.33.23490
full_text_status: none
publication: International Journal of Engineering and Technology(UAE)
volume: 7
number: 4
pagerange: 78-82
refereed: TRUE
issn: 2227524X
citation:   Isa, N.H.M. and Othman, M. and Karim, S.A.A.  (2018) Multivariate matrix for fuzzy linear regression model to analyse the taxation in Malaysia.  International Journal of Engineering and Technology(UAE), 7 (4).  pp. 78-82.  ISSN 2227524X