ABSTRACT
Heart disease is one of the number one causes of death in Indonesia. The high number of deaths due to heart disease is due to the lack of cardiologists, the lack of public awareness to do regular heart health checks, and the poor lifestyle of patients. Heart disease has a high mortality rate in both developed and developing countries. Worldwide, the number of patients with this disease continues to grow every year. Cigarette smoking has widely become one of the causes of death in the world, and smoking is a behavior that is harmful to health. Adverse habits and routines have the power to damage a person's health such as smoking, which is a habit that makes it easier for a
person to get cardiovascular disease. A prediction system using the Support Vector Machine method based on Particle Swarm Optimization, known to have high data classification results, applies to heart disease prediction. Then, this study aims to create a computational system that can see smokers' risk of developing heart disease.

Keywords:
Heart Disease, Cigarette Smoking, Support Vector Machine, Particle Swarm Optimization