Penerapan Bayesian Network Pada Sistem Pakar Ekspresi Wajah dan Bahasa Tubuh Melalui Pengamatan Indra Penglihatan Pada Foto - Muhammad Adiputra; Rekyan Regasari Mardi Putri; Suprapto Suprapto (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2018)
Facial expression and body language is a non-verbal language that can describe the real emotion in a person. Movement on facial expressions and body language shown by humans not only contains. Other than that, for some cases it needs a combination of facial expressions with body language to know the hidden meaning in it. The expert system of facial expression and body language is the application of probabilistic theory and graph theory on the bayesian network method. The purpose of making this expert system is to identify the meaning of emotion that a person shows through facial expression and body language. There are 7 expressions of feelings and emotions that becomes the system output, that are: lie, honest, angry, sad, fear, happy, and suprised. Based on testing of variation data training, it was found that the amount of data training and variation of it also affected the accuracy of the system result. In addition, it is also known that more data training used and more varied, it will increase the level of accuracy. While based on the results of the test using the f-measure method conducted on 5 cases containing 28 images, where each picture shows facial expression and body language of 5 different people, obtained the average of 80.47% precision, 86.34% recall, and an accuracy level for f-measure is 80.31%.