It has been successfully designed an Electronic Nose (e-Nose) instrumentation system consisting of 6 MQ gas sensors, namely, MQ2, MQ4, MQ5, MQ7, MQ9, MQ135. The E-nose system is used to identify halal-haram food. This E-Nose system uses an Arduino Nano microcontroller. The Graphic User Interface (GUI) system is built with Visual Studio 2008. Then, the data responses will be evaluated by using 2 patterns recognition methods called Principle Component Analysis (PCA). The classification results can be explained by the value of the score plot on the PCA of the data. PC1 accounts for 19% of the variance, and PC2 accounts for 5% of the variance, data obtained is stored and displayed on personal computers in Excel format. Each sample was tested for up to ten repetitions. The data obtained from the six sensors in the e-nose was processed using Minitab 18 and it was necessary to obtain classification data on lard, pig oil, and sample B, which were fried crackers using pork oil.