Microarray experiment's data contain errors, from various sources. The process of identifying and adjusting of systematic variation in intensities between samples on the same slide is known as normalization. We implemented a java application with graphical user interface that allows easy evaluation of errors and the role of hybrid normalization methods to remove the systematic errors from the experiment's data. We calculated true hybridization intensity then applied different additive and multiplicative errors and computed the normalized intensity logged ratio using background subtraction, self-normalization method and dye-flip technique. Results show the efficiency of hybrid normalization method in order to remove error rates from the intensity values.