We establish novel entropy functions based on some types of generalized fractional derivatives. Classic entropy functions are included in the results obtained in this paper. As an application in information theory and probability theory, we use these entropy functions to measure the uncertainty and similarity of data collected from crop-sown areas in 32 regions. For doing this, the approach of hierarchical clustering with the average-linkage method is used and three visual dendrograms are offered in the end.