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(Universitas Ahmad Dahlan, Indonesia)(2) Abdul Fadlil
(Universitas Ahmad Dahlan, Indonesia)(3) * Denis Prayogi
(Universitas Ahmad Dahlan
STMIK PPKIA Tarakanita Rahmawati, Indonesia)*corresponding author
AbstractMachine learning is one of artificial intelligence that is used to solve various problems, one of which is classification. Classification can separate a set of objects based on certain characteristics. This study discusses the classification of objects in the form of facial images with the aim of the system being able to recognize a person's face to access a room for security reasons. The application of machine learning using the support vector machine algorithm with the support vector classifier technique is implemented on a raspberry pi-based security device. Â The results of training using this algorithm produce a model with 99% accuracy in 0.10 seconds based on testing data of 525 face images. The model evaluation got 99% precision, 99% recall, and 99% f1-score. Testing the model made from the training process using the raspberry pi model 4b is can recognize facial images in real-time. Â If the security device detects someone at the door and then recognizes the face image then room access will be granted and an alarm is activated indicating the door is open.
KeywordsMachine Learning; Support Vector Machine; Face Recognition; Raspberry Pi; Scikit-learn
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DOIhttps://doi.org/10.29099/ijair.v7i1.321 |
Article metrics10.29099/ijair.v7i1.321 Abstract views : 1141 | PDF views : 425 |
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