Machine Learning Approach of Obesity Level Classification: A Systematic Literature Review of Methods and Factors

Steven Marcelino Tandiono (Universitas Multimedia Nusantara, Indonesia)
Samuel Ady Sanjaya (Universitas Multimedia Nusantara, Indonesia)

G-Tech : Jurnal Teknologi Terapan
Vol 8 No 1 (2024): G-Tech, Vol. 8 No. 1 Januari 2024

The high prevalence of obesity over the years has become a global concern, as obesity contributes to an increased risk of many deadly diseases, such as diabetes, heart disease, and some cancers. This condition has become a serious concern for public health authorities, researchers, and the general public. Therefore, a comprehensive and effective approach is needed to tackle this obesity problem. Machine learning can be the answer to the required approach as it offers a method to predict the risk level of obesity through identifying the risk causes quickly and accurately. Through this approach, the most influential factors in obesity risk can be identified to aid in the development of more effective prevention and intervention strategies. Understanding the correlation between risk factors and obesity will hopefully lead to better solutions in addressing global obesity.