1. Start with a truly random seed between 0 and 15.
2. Increment it each time to generate a random number, modulo 16.
Suppose you start at 11. Your sequence of random numbers will be 11, 12, 13, 14, 15, 1, 2, 3 ....
This is obviously not very random. But look at the entropy of it. All values between 0 and 15 are equally likely, so this will have the maximum possible entropy: 4 bits.
The problem here is that, for entropy to be an accurate measurement of information content, you have to assume that you're measuring independent identically distributed random variables. The outputs from a pseudo-random number generator are not independent.
The generator you are talking about is far from producing a uniform distribution (which would have maximum entropy) jointly over the n-dimensional hypercube that would represent a sequence of n draws from your generator, so it has less entropy and is thus "less random" than the distribution you'd get from n independent draws from a perfect rand().