Penentuan Tes Kepribadian Calon Mahasiswa Berdasarkan Sidik Jari Menggunakan Minutie dan Support Vector Machine
Abstract
Every human being is given its own uniqueness by an almighty god, one of which is a part of the body organs such as the fingerprint pattern of the hand, the fingerprint pattern of each human being determines personality, this can be known from many previous studies, which use fingerprints or someone's detection by the police to capture the perpetrators with the biometry approach in the form of footprint fingerprint records attached to other objects. Determination of a person's personality can be known through fingerprints, and also can adjust prospective students in choosing the study program correctly. Fingerprint student personality identification application provides convenience in determining the choice of prospective students of the study program. The minutie method and the Support Vector Machine algorithm are used in clustering personalities according to training data in the application. The minutie test on the fingerprint pattern shows 100% compatibility, with a precision input image source. SVM algorithm in testing reached 80,9% in grouping personality types accordingly.
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References
I. G. Sujana, E. Putra, I. K. G. D. Putra, and I. P. A. Bayupati, “Pengenalan Kepribadian Seseorang Berdasarkan Sidik Jari Dengan Metode Fuzzy Learning Vector Quantization Dan Fuzzy Backpropagation,” Maj. Ilm. Tek. Elektro, vol. 13, no. 2, 2014.
S. Saparudin and E. Rasywir, “Pengenalan potensi anak melalui sidik jari Menggunakan algoritma voting feature intervals 5 (vfi5),” J. Res. Comput. Sci. Appl., vol. 1, no. 1, pp. 25–30, 2012.
Eileen Rachman & Emilia Jakob, “No Title,” Kepribadian Kunci sukses, 2015.
Fitriana Monica Sari, “No Title,” Biar Lolos, Kenali Bentuk Tes Psikologi ini, Liputan 6, 2019.
J. Informatika, L. Hakim, U. B. Mulia, and U. B. Mulia, “Penilaian Kinerja Dosen Tetap Menggunakan K-Mean,” vol. 13, no. April, pp. 87–94, 2019.
S. Shabri, “Hubungan Tipe Kepribadian Dengan Motivasi Belajar Pada Mahasiswa Kurikulum Berbasis Kompetensi Fakultas Keperawatan Universitas Syiah Kuala,” Idea Nurs. J., vol. 7, no. 2, pp. 1–12, 2016.
A. P. Nasution, A. B. Osmond, and R. E. Saputra, “Deteksi Kepribadian Anak Dengan Pengolahan Citra Sidik Jari Menggunakan Metode Minutiae Detection Of Children ’ S Personality With Fingerprint Image,” vol. 5, no. 3, pp. 6102–6109, 2018.
E. P. P. Sandri Titik Wulandari, Ernawati, “aplikasi biometrika pengenalan citra sidik jari dengan metode minutiae dan artificial neural network backpropagation,” J. Rekursif, vol. 5, no. 1, pp. 107–120, 2017.
M. R. Syahziar, K. M. Lhaksamana, and S. Al Faraby, “Klasifikasi Sidik Jari Menggunakan Metode Minutiae,” e-Proceeding Eng., vol. 5, no. 1, pp. 1803–1810, 2018.
Lukman, “Penerapan Algoritma Support Vector Machine ( SVM ) Dalam Pemilihan Beasiswa : Studi Kasus SMK Yapimda,” Fakt. Exacta, vol. 9, no. 1, pp. 49–57, 2016.
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