In this research, Method that used to select the optimal parameter is Taguchi Method while for feature selection is FCBF where will applied in high- dimensional data. In addition, computing process becomes less efficient is caused by large number of features so best feature selection also needed to do. Hence, the uses of selection method of optimal parameter as grid search and Taguchi approach is needed to be applied to obtain optimal parameters. Effect giving optimal parameters can improve the classification accuracy. SVM has some advantage in terms of classification, however still has problems that must be considered, one of them is related to select the optimal parameter of SVM. The principle of SVM is as follows: given set of classified data is trained by algorithm to obtain a set of classification models which can help to predict the category of newdata. Support vector machine (SVM) is one of superior machine learning method with great results in classification and prediction. Hypothesis of this thesis is the analysis and implementation of algorithms K-Nearest Neighbor optimized with Genetic algorithms can predict the level of performance of a high- dimensional disease data above 75%. Algorithm K-Nearest Neighbor (KNN) is a data mining algorithm that can be used to classify the data and Genetic Algorithm (GA) can help maximize the classification accuracy of a subset of attributes. Genetic Algorithm (GA) is one of the EAs very useful algorithm for solving the problem in the search process (searching) and process optimization (optimization). Evolutionary Algorithms (EAs) is a population-based meta heuristic optimization algorithm generic that can help in reducing the dimensions of data mining. Evolutionary of Data Mining can be the one solution that can overcome the problems of high dimensional data. Curse of dimensionality are the real problems related to high dimensional data, so that the data processing becomes less effective. In the data processing, the data has a high dimensionality and it’s really difficult to handle. Data mining can understand certain techniques in data processing, in order to obtain the hidden information.

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