# how does splitting at a node occur in a decision-tree with non-categorical data?

According to a website (:http://dataaspirant.com/2017/01/30/how-decision-tree-algorithm-works/) , these values are chosen randomly for both gini index and Entropy method:

I don't think this is the case with any optimized way of creating a decision tree. In this image(different example) the value is 2.45 for the root node:

Was this value chosen randomly like explained in the website? If not and the value is not chosen randomly then how is it calculated?