Stroke is one of the leading causes of death in the world. The previous study had shown that EEG (Electroencephalogram) was a promising tool to detect stroke since it is non-invasive and cheap. So, the EEG analysis method needs to be more explored to give an accurate prognosis assessment. Previously, complexity analysis, such as Fuzzy Approximate Entropy (fApEn), had been successfully differentiated between control and patients with Alzheimer's Disease. Thus, this study used fApEn to analyse the changes of electroencephalography complexity in Acute Ischemic Stroke (AIS) during hyperventilation and photic stimulation, which are a general protocol to investigate the abnormality in EEG. Photic stimulation conducted using white light that flashed with frequency 5Hz, 10Hz, and 15Hz consecutively for three minutes and then continued by hyperventilation for three minutes, approximately. This study compared the fApEn value from healthy subjects with AIS patients. The result showed that patient with AIS tended to conduct the lower and higher fApEn value compared to the healthy subject. The lower value of fApEn occurred because of the presence of the slow-waves on the EEG, while the higher fApEn indicated the epileptiform activity during the recording. The increment of the slow-waves and the presence of epileptiform activity could be considered as the characteristic of stroke even though its appearance is uncertain. However, complexity analysis of EEG could be useful in differentiating the healthy subject and patient with stroke or classifying the severity level of the stroke to improve stroke management.