Adjustment of the Height Triangular Fuzzy Regression as Early Awareness of Breast Cancer

• Published in: Journal of Advanced Research in Applied Sciences and Engineering Technology
• Main Author: Lidinillah Z.; Shafi M.A.; Rusiman M.S.; Nasibov E.; Abdul Rashid N.F.; Othman S.
• Format: Article
• Language: English
• Published: Semarak Ilmu Publishing 2025
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209215656&doi=10.37934%2faraset.52.2.189197&partnerID=40&md5=f572cf193e06f81d0f620bb38de9761c

Breast cancer is the most popular malignancy among Malaysian women. In Malaysia, approximately one in every 19 women is at risk. Breast cancer is the most common cancer among Malaysian women (32.9%), followed by colorectal (11.9%) and ovarian cancers (7.2%). Many cases are found to be advanced, with considerable tumour development or metastasis to untreatable locations and unaware of the factors. This study aims to determine the best height triangular fuzzy regression model by adjustment between 0 – 1 and measure the value of statistical error using mean square error (MSE) and root mean square error (RMSE). Secondary data was used where 569 patients having BREAST cancer and receiving treatment in hospitals was recorded by nurses and doctors. The patient data for breast cancer were analysed using MATLAB, SPSS, and Microsoft Excel. Based on the results, H = 0 of fuzzy linear regression is the best model to predict the breast cancer awareness with lowest value of MSE and RMSE by 1.455 and 1.206 respectively. Malaysians must be aware of the warning factors of breast cancer to increase survival and minimise death rates. © 2025, Semarak Ilmu Publishing. All rights reserved.