Multivariate Matrix for Fuzzy Linear Regression Model to Analyse The Taxation in Malaysia - Hidayah Mohamed Isa, Noor; Othman, Mahmod; Ariffin Abdul Karim, Samsul (International Journal of Engineering and Technology, 2018)
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  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.