K-Nearest Neighbor algorithm is adapted to predict the location of the user in the experimentation area. Indoor environment and resistance of an indoor environment such as walls and movement of objects adversely affect the accuracy of the location prediction. The effect of number of RSS sample collected during the offline and online phase to the accuracy of the location predicted is evaluated.