Sistem Absensi Mahasiswa Berbasis Dorsal Hand Vein Menggunakan Local Binary Patterns dan Fuzzy k-NN - Suharsono Bantun; Jayanti Yusmah Sari; Noorhasanah Z; Mardianto Mardianto; Aspian Achban (JATISI (Jurnal Teknik Informatika dan Sistem Informasi), 2022)
After WHO announced COVID-19 as a pandemic in 2020, universities began to implement online learning, after 1 year had passed, limited face-to-face learning would begin again by prioritizing the health and safety of campus residents. The offline lecture attendance system manually by signing the attendance sheet is at risk of becoming a medium for transmitting the virus because it is touched by many lecturers and students. Biometric systems are widely applied in various fields such as security systems and employee attendance. However, it has several weaknesses, such as the possibility of sabotage in fingerprints and palm geometry, difficulty in recognizing facial objects using accessories such as hats and glasses as well as changing expressions and expensive acquisition tools in retina-based recognition applications. This study uses Local Binary Patterns (LBP) to identify the dorsal hand vein. LBP is used as a feature extraction method to optimize the feature value of the vein texture in order to obtain good accuracy and fast processing speed. To match the dorsal vein features of the test image and the image in the database, the Fuzzy k-NN method is used. The test results show a good recognition accuracy of 90.67%.