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EEG instrument (electroencephalography) is an instrument used as a recorder of brain activity by showing brain waves. The principle of EEG is to detect and to find out changes in each neuron cell that is characterized by waves and interictal waves on the EEG (electroencephalogram) results. Collection of brain signal data is recorded so as to produce imagery motor data. In this study using multiclass EEG signal data (four classes of body movement movements) that will be processed on the EEG signal classification system based on body movement patterns in MxNxT format, where M is the number of channels, N is the number of samples per channel and T is the number of trials. The initial stage of the signal is filtered using butterworth to eliminate noise. EEG signal feature extraction uses the CSP method to get the required features and the last stage uses fuzzy and ANN. The results of the classification of ANN 83% and Fuzzy 78.3%, but in some cases Fuzzy produces significant accuracy.