This work proposes the use of data division and if statements in a programming language, as an effective classifier in Artificial Neural Network. The Standing and Katz chart was digitized to obtain input (pseudo reduced temperature and pressure) and output (gas compressibility factor) data points, which was used in developing the artificial neural network. A total of 114,120 input data points and 57,060 output data points were used. The dataset was divided into 4 groups, and each of the groups was assigned a neural network that corresponds to the value range of the grouped data using a Matlab nnet tool box.