Irawan Dwi Wahyono, Muhammad Ashar, Irham Fadlika, Khoirudin Asfani, Djoko Saryono, Sunarti
Ubiquitous was increasingly used in industrial technology 4.0, especially those aimed at facilitating human's activities. This was due to the fact that ubiquitous technology was small and inexpensive, but had limited resources. Research on ubiquitous had been widely developed, especially in the use of sensors in ubiquitous. Sensor optimization of facial detections had also been done a lot. High computation for face detection and facial emotions caused overload on ubiquitous. This was caused by limited resources. These limitations caused a decrease in the level of face detection accuracy. This research developed new techniques for face detection, especially emotions by using ubiquitous. This facial emotion detection used a hybrid Computational Intelligence algorithm whose process was done on ubiquitous. Fuzzy C-Mean algorithm functioned as a color grouping in face detection. The results of this color grouping were histograms. After the histogram process was complete, numerical values were obtained for each photo of facial emotion. Each facial emotion had a histogram numeric value which was used as a data set in this study. Experimental testing on this ubiquitous device produced an accuracy value of 77.5%. © 2019 IEEE.
Universitas Negeri Malang, Malang Jawa Timur, Indonesia
