Application of Fuzzy Hexagonal Numbers in the Diagnosis of Respiratory Tract Infections, Common Cold, and Pharyngitis Callista Monalisa(a), Mashadi(b*)
a)Department of mathematics, University of Riau, Jalan HR. Soebrantas KM. 12,5, Pekanbaru 28293, Indonesia
b)Department of mathematics, University of Riau, Jalan HR. Soebrantas KM. 12,5, Pekanbaru 28293, Indonesia
*mashadi.mat[at]gmail.com
Abstract
Hexagonal fuzzy numbers extend the concept of pentagonal fuzzy numbers by introducing a six-parameter structure that provides a more flexible representation of uncertainty. Although several algebraic models for hexagonal fuzzy numbers have been proposed, there is still no unique inverse defined for all cases. This paper presents an alternative algebraic approach for handling hexagonal fuzzy numbers and demonstrates its practical application in medical diagnosis. Specifically, the study integrates hexagonal fuzzy numbers within fuzzy soft set matrices to diagnose respiratory tract infections (ISPA), the common cold, and pharyngitis. The research process involves converting interview and observation data into numerical values ranging from 0 to 10, which are then transformed into hexagonal fuzzy numbers. These are represented in a hexagonal fuzzy soft set (HxFSS) and further modeled as a hexagonal fuzzy soft matrix (HxFSM). The resulting framework provides more accurate and reliable diagnostic evaluations under uncertainty.
Keywords: fuzzy soft matrices, hexagonal fuzzy soft matrices, medical diagnoses
