Emotion and Attention of Neuromarketing Using Wavelet and Recurrent Neural Networks

One method concerning evaluating video ads is neuromarketing. This information comes from the viewer's mind, thus minimizing subjectivity. Besides, neuromarketing can overcome the difficulties of respondents who sometimes do not know the response to the video ads they watch. Neuromarketing involves information from what customers think is captured by an Electroencephalogram (EEG) device. Meanwhile, if the electrical signal information in the brain is corresponding to an understanding of one's psychology, it is called neuropsychology. This field consists of emotions, attention, and concentration variables. This research offered neuromarketing base on emotion and attention of EEG signal using Wavelet extraction and Recurrent Neural Networks. Measurement of EEG variable every two seconds while watching video ads. The results showed that Wavelet and Recurrent Neural Networks could provide training data accuracy of 100% and 89.73% for new data. The experiment also gave that the RMSprop optimization model for the weight correction contributed to higher correctness of 1.34% than the Adam model. Meanwhile, using Wavelet for extraction can increase accuracy by 5%.