COMPARATIVE ANALYSIS OF STROKE CLASSIFICATION USING THE K-NEAREST NEIGHBOR DECISION TREE, AND MULTILAYER PERCEPTRON METHODS

Stroke has become a serious health problem; the main cause of stroke is usually blood clot in arteries that supply to brain. Strokes can also be caused by bleeding when vessels burst and leaks into In one year, about 12.2 million people will have their first stroke, 6.5 die from stroke. More than 110 worldwide had Handling done quickly minimize level brain damage potential adverse effects. Therefore, it very important predict whether patient experience The K-Nearest Neighbor, Decision Tree, Multilayer Perceptron algorithms are applied as classification method identify symptoms patients achieve an optimal accuracy level. results making three quite good, where Neighbor (K-NN) value 93.84%, Tree 93.97%, (MLP) 93.91%. best algorithm with difference no more 0.10% two used.