TY - GEN
T1 - Personality Classification from Online Handwritten Signature using k-Nearest Neighbor
AU - Laga, Harris Teguh
AU - Pane, Evi Septiana
AU - Wibawa, Adhi Dharma
AU - Purnomo, Mauridhi Hery
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Signature is the representation of a personal identity that written on a selected medium. Signature can describe people's personality, which includes character, potential, motivation, emotional stability, mental state, intellectual tendencies, and one's work habits. Understanding people's personality is useful to show personality traits in criminology, medical science, and counseling. Previous research has investigated the relationship between online signature and personality by using tablet digitizer. In this paper, we are improving the method by increasing the amount of respondents, using a classification algorithm, and using psychological tests for validation named Big Five Inventory Test (BFI Test). The two best features pressure and speed have been analyzed and classified using k-Nearest Neighbor (kNN). The highest classification accuracy from kNN is 87.5%. From 40 respondents who were involved, 90% were confirmed well with BFI test for the first or second dominant personality. As a conclusion, this research shows that online signature analysis could predict personality with high accuracy.
AB - Signature is the representation of a personal identity that written on a selected medium. Signature can describe people's personality, which includes character, potential, motivation, emotional stability, mental state, intellectual tendencies, and one's work habits. Understanding people's personality is useful to show personality traits in criminology, medical science, and counseling. Previous research has investigated the relationship between online signature and personality by using tablet digitizer. In this paper, we are improving the method by increasing the amount of respondents, using a classification algorithm, and using psychological tests for validation named Big Five Inventory Test (BFI Test). The two best features pressure and speed have been analyzed and classified using k-Nearest Neighbor (kNN). The highest classification accuracy from kNN is 87.5%. From 40 respondents who were involved, 90% were confirmed well with BFI test for the first or second dominant personality. As a conclusion, this research shows that online signature analysis could predict personality with high accuracy.
KW - BFI Test
KW - Classification Algorithm
KW - Online Signature
KW - kNN
UR - http://www.scopus.com/inward/record.url?scp=85078400038&partnerID=8YFLogxK
U2 - 10.1109/ISITIA.2019.8937180
DO - 10.1109/ISITIA.2019.8937180
M3 - Conference contribution
AN - SCOPUS:85078400038
T3 - Proceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
SP - 404
EP - 409
BT - Proceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
Y2 - 28 August 2019 through 29 August 2019
ER -