Multivariate matrix for fuzzy linear regression model to analyse the taxation in Malaysia

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

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

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.

Item Type: Article
Additional Information: cited By 2
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:37
Last Modified: 09 Nov 2023 16:37
URI: https://khub.utp.edu.my/scholars/id/eprint/10705

Actions (login required)

View Item
View Item