SUMMARY
Abstract - Heart attack is the deadliest disease in the world including Indonesia. According to the report the heart Foundation Indonesia showed that the death toll reached more than 27 of 100 people due to heart disease. Early detection of heart disease is very needed considering the many people who suffer from heart disease on average already advanced stage. Intelligent system of early detection of heart disease is a method to know the symptoms that need to be alerted immediately so that heart disease could be known as early as possible. The methods used in this study using Decision Tree Classifier, the datasheet used are taken from the UCI Machine Learning Repository consisting of thirteen 270 instance, attribute input and 1 target attribute.The results of this research will result in a decision tree that can help the community and or used as a reference for a doctor in diagnosing early heart disease. The second is this research can also predict a person can be diagnosed with heart disease or not by giving the input a few symptoms that are already established, the research results cannot replace an existing heart examination but at least it can help society in General nor the doctor.