Obesity Prediction with Classification Model Based on Anthropometric Data and Lifestyle Factors using Random Forest
Year: 2025
Type: article
Abstract: Overweight and obesity have become a significant health problem worldwide, including in Indonesia. This study aims to solve this problem by developing a machine learning model based on the Random Forest Classifier algorithm. This model can be used to classify various types of obesity based on relevant variables. This study uses data from the trusted Kaggle data source to find and manage community problems with obesity and overweight. The machine learning approach allows this model to predict obesity types with high accuracy, exceeding 90%. The advantage of this approach is that it can create solutions based on a person's gender, age, weight, and height, as well as other relevant factors
Source: Jurnal Ilmiah Teknik
Authors: Rizky Adha Hardiman, Ari Rosemalatriasari
Institution: Gunadarma University
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4411344340