A statistical fuzzy clustering approach to analyze the characteristics of the number of new cancer cases in Asia for Health

¹ Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Negeri Surabaya, Surabaya, East Java, Indonesia
² Department of Nursing, Faculty of Health and Education, Manchester Metropolitan University, Bonsall St, Manchester, M15 6GX, United Kingdom

^* Corresponding author: ayuninsofro@unesa.ac.id

Abstract

Cancer is a disease characterized by the uncontrolled growth and spread of abnormal cells in an organ of the human body. Asia is the continent that has the most significant number of new cases of cancer, with a percentage of 49.3% of the number of cancer patients in the world. Preventive action to deal with the spread of cancer is the responsibility of the government to improve the quality of health in the country, so it is necessary to take action to prevent the spread of cancer and help archieve the Sustainable Development Goals (SDGs) at the third point in the field of health. One of them is by determining the characteristics of the cancer and clustering countries in Asia based on their characteristics. This article will discuss the clustering of countries in Asia using fuzzy clustering in the form of fuzzy k-means, fuzzy Gustafson-Kessel babushka and fuzzy k-medoids. the results obtained from the analysis show that using fuzzy k-means will have a more excellent fuzzy silhouette index value compared to fuzzy Gustafson-Kessel babushka and fuzzy k-medoids, which is 0.6313.