Malik Akbar, Maulana (2024) PROTOTYPE FINGEPRINT & FACIAL ATTENDANCE SYSTEM BERBASIS RASPBERRY PI DENGAN METODE SUPPORT VECTOR MACHINE (SVM). S1 thesis, UNIVERSITAS SULTAN AGENG TIRTAYASA.
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Abstract
Biometrics is a part of the field of technology that approaches recognition systems designed to be able to recognize and dentify characteristic parts of the human body. Parts of the body in humans that are used such as faces and fingerprints are used as patterns to carry out needs in the identification process, then these body parts are used as objects for means of identifying presence. Raspberry Pi is used as a tool that processes the integrity of biometric objects that are used with the help of a webcam and fingerprint sensor to recognize someone's face and fingerprints. Then a Raspberry Pi-based Face Attendance System Prototype was designed using the Support Vector Machine method. The Support Vector Machine method based on supervised learning is used to solve classification and regression problems. By using the Support Vector Machine algorithm in MATLAB to process facial images, it is known that the accuracy value obtained by testing 25 students with facial images obtained 375 images divided from one student consisting of 15 images. 250 images of training data were tested with a result of 65.20% and 125 images of test data with a result of 66.40%.
| Item Type: | Thesis (S1) | |||||||||
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| Additional Information: | Biometrik merupakan salah satu bagian pada bidang teknologi yang melakukan pendekatan mengenai sistem pengenalan yang dirancang untuk dapat mengenal dan mengidentifikasi bagian karakteristik tubuh pada manusia. Bagian tubuh pada manusia yang digunakan seperti wajah dan sidik jari dijadikan pola untuk melakukan kebutuhan dalam proses identifikasi, maka bagian tubuh tersebut dijadikan objek terhadap sarana untuk melakukan identifikasi kehadiran. Raspberry Pi igunakan sebagai alat yang memproses integritas terhadap objek biometrik yang digunakan dengan bantuan webcam dan sensor sidik jari terhadap mengenali wajah dan sidik jari dari sesorang. Maka dirancanglah Prototype Face Attendance System berbasis Raspberry Pi dengan metode Support Vector Machine. Metode Support Vector Machine berbasis supervised learning igunakan memcah masalh klasifikasi dan regresi. Dengan digunakan algoritma Support Vector Machine pada MATLAB untuk mengolah gambar wajah sehingga diketahui nilai akurasi yang didapat dengan melakukan pengujian terhadap 25 mahasiswa dengan gambar wajah yang didapat 375 gambar yang terbagi dari satu mahasiswa terdiri dari 15 gambar. Dilakukan pengujian data latih sebanyak 250 gambar dengan hasil 65,20% dan data uji sebanyak 125 gambar dengan hasil 66,40% | |||||||||
| Uncontrolled Keywords: | Attendance system, Raspberry Pi, Fingerprint Recognition, Face Recognition, MATLAB, Support Vector Machine. Sistem absensi, Raspberry Pi, Pengenalan Sidik Jari, Pengenalan Wajah, MATLAB, Support Vector Machine. | |||||||||
| Subjects: | T Technology > T Technology (General) | |||||||||
| Divisions: | 02-Fakultas Keguruan dan Ilmu Pendidikan 02-Fakultas Keguruan dan Ilmu Pendidikan > 83201-Jurusan Pendidikan Vokasional Teknik Elektro |
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| Depositing User: | Maulana Malik Akbar | |||||||||
| Date Deposited: | 20 Feb 2024 15:50 | |||||||||
| Last Modified: | 21 Feb 2024 09:42 | |||||||||
| URI: | http://eprints.untirta.ac.id/id/eprint/33033 |
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