BODY MASS INDEX CLASSIFICATION COMPARISON IN PREDICTING OBESITY AMONG ADULTS INDONESIAN USING K-MEANS CLUSTERING DATASET

The dataset consists of anthropometric and demographic data collected from adult individuals in Indonesia. It includes the following variables: Gender: Indicates the gender of the individual, categorized as Male or Female. Age: Represents the age of the individual in years. Height: The height of the individual in meters. Weight: The weight of the individual in kilograms. BMI (Body Mass Index): Calculated using the formula BMI=Weight (kg)Height (m)2BMI=Height (m)2Weight (kg). Label: The BMI classification of the individual, categorized into classes such as Normal and Obese. The dataset provides a basis for clustering and classification analysis to explore patterns in BMI distributions and predict obesity using the K-Means algorithm. It highlights gender and age-related BMI variations across the Indonesian adult population, supporting the evaluation of clustering performance in predicting obesity trends.