Predictive Analytics of Comparison Fuzzy Modelling Towards Symptoms of Colorectal Cancer in Malaysia

Authors

  • Muhammad Ammar Shafi Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia
  • Nur Azia Hazida Mohamad Azmi Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia
  • Mohd Saifullah Rusiman Department of Mathematics and Statistics, Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia
  • Aliya Syaffa Zakaria Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia
  • Mohd Zarir Yusoff Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia
  • Hafizah Zulkipli Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia
  • Nor Kamariah Kamaruddin Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia

DOI:

https://doi.org/10.37934/araset.47.2.213222

Keywords:

Colorectal cancer (CRC), Prediction model, High-risk symptom, Statistical errors measurement

Abstract

Colorectal cancer (CRC) is a cancer that begins in the colon and rectum of the human body and is the third leading cause of death among cancer patients. Colorectal cancer develops when cells in the body begin to proliferate uncontrollably with such symptoms. However, the high-risk symptoms of CRC in Malaysia are still ambiguous and unclear. The problem of using linear regression arises with the use of uncertain and imprecise data. Since the fuzzy set theory’s concept can deal with data not to a precise point value (uncertainty data), this study uses comparison fuzzy modelling as predictive analytics to predict the high-risk symptoms that contribute to the development of colorectal cancer in Malaysia. Secondary data of 180 colorectal cancer patients who received treatment in a general hospital with seventeen independent variables with different combinations of variable types were considered. Other than that, the parameter, error, and explanation for the model were included using two measurement statistical errors. Fuzzy linear regression with symmetric parameters found ovarian symptom is the high-risk symptom to develop colorectal cancer. The weightage value is 25.73, with the results of the least value of the mean square error (MSE) value being 98.212 and the root mean square error (RMSE) value being 9.910.

Author Biographies

Muhammad Ammar Shafi, Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia

ammar@uthm.edu.my

Nur Azia Hazida Mohamad Azmi, Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia

nuraziahazida@gmail.com

Mohd Saifullah Rusiman, Department of Mathematics and Statistics, Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia

saifulah@uthm.edu.my

Aliya Syaffa Zakaria, Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia

syaffayila98@gmail.com

 

Mohd Zarir Yusoff, Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia

zarir@uthm.edu.my

 

Hafizah Zulkipli, Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia

hafizahz@uthm.edu.my

Nor Kamariah Kamaruddin, Department of Technology and Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Johor, Malaysia

nkamariah@uthm.edu.my

 

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Published

2024-06-28

How to Cite

Muhammad Ammar Shafi, Nur Azia Hazida Mohamad Azmi, Mohd Saifullah Rusiman, Aliya Syaffa Zakaria, Mohd Zarir Yusoff, Hafizah Zulkipli, & Nor Kamariah Kamaruddin. (2024). Predictive Analytics of Comparison Fuzzy Modelling Towards Symptoms of Colorectal Cancer in Malaysia. Journal of Advanced Research in Applied Sciences and Engineering Technology, 47(2), 213–222. https://doi.org/10.37934/araset.47.2.213222

Issue

Vol. 47 No. 2: May (2025)

Section

Articles