Implementation of Eigenface Method in Improving Security in a Smart Home Systems - Abdurrasyid Abdurrasyid; Riki Ruli Afandi Siregar; Indrianto Indrianto; Meilia Nur Indah Susanti (Pancaran Pendidikan, 2018)
Based on data that was extracted from Indonesia Central Bureau of Statistics there were has been theft cases as much as 125.869 times during 2015, consists of Crime against Property / Goods with Violence 11.856 cases, and Crimes against Property / Goods Non-Violent 114.013 cases, theft often occurs in empty homes that no occupants, theft is also common in homes that have security cameras, cameras that were installed cannot provide prevention or warning to homeowners. It can be anticipated if the homeowner gets information about the condition of the house in real time wherever he is. This technology is designed to created smart home system that was integrated by the security method especially in face recognition, Eigenface method as the image processing method used to detect home occupants to avoid thieves, the core of this method is to compare the eigenface value of the captured image with the eigenface value present in the database, the smaller difference between the eigenface training image in the database with the eigenface test face it can be concluded that the image has a higher similarity, greater differences,  will make the system detect that an unknown person is entering the house, and will send a warning message to the homeowner via cell phone about danger that is occurs.