<![CDATA[The growth of technology is developing very rapidly in various fields, ranging from industry, offices, government, to education. One interesting innovation is the application of facial recognition to an Android-based attendance system. This system allows attendance to be carried out by scanning employee faces using Android devices in certain areas such as offices or companies. By using this technology, the attendance process which is usually done manually or using fingerprints can be optimized, thereby reducing the risk of long queues when employees are present together. In some offices, attendance is still done manually by filling in attendance books or using fingerprints. This method often causes problems, especially when many employees come at the same time. The queues that form will of course interfere with their productive time. Therefore, to overcome this problem, an Android-based attendance application is needed that integrates facial recognition technology. This application is designed so that it can only be accessed in an office environment, with certain area coverage settings. This study uses the Convolutional Neural Network (CNN) algorithm which is effective for image processing in facial recognition. In addition, researchers also apply the GPS Locking or Geotagging method to ensure that attendance can only be carried out in predetermined areas, thereby increasing the security and accuracy of attendance data. The dataset used in this study consists of facial images, where each individual is photographed in five different angles to improve the accuracy of the system. The results of this study are expected to create a more efficient and effective attendance system. By simplifying the attendance process, this technology not only saves time but also increases employee satisfaction, because they no longer have to face long queues. This is a step forward in utilizing technology to improve human resource management in the digital era.]]>
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