Pengenalan Kepribadian Seseorang Berdasarkan Pola Tulisan Tangan Menggunakan Jaringan Saraf Tiruan

Mutia Fadhilla, Maksum Ro’is Adin Saf, Dadang Syarif Sihabudin Sahid

Abstract


Graphology is a study of representing personality based on handwriting. Individual’s handwriting is unique and has own feature that it can be analyzed to understand personality. Graphology is used in some fields such as staffing, determining interest and talent. Some researches in graphology using artificial intelligence have been studied before. However, most of the researches still used one handwriting feature and did not classify into personality type. In this study, using some features of handwriting, i.e. left margin, right margin, size, and slant to classify personality type. Personality is classified based on Myers-Briggs Type Indicator (MBTI) using Back Propagation and Learning Vector Quantization method. The result shows that Learning Vector Quantization has better performance, with 90% accuracy, than Back Propagation, which has 82% accuracy.

Keywords


Grafologi, Kepribadian, Jaringan Saraf Tiruan, Back Propagation, Learning Vector Quantization.

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References


C. M. Bishop, Pattern Recognition and Machine Learning, New York: Springer Science+Business Media, 2006.

G. K. Arridho, ”Analisis Pen Pressure Tulisan Tangan untuk Mengidentifikasi Kepribadian Seseorang Menggunakan Support Vector Machine (SVM),” Journal of Informatics and Technology, Vol 2, No 3, pp. 66-67, 2013.

E. Prasetiawan, ”Analisis Pola Garis Dasar Tulisan Tangan Untuk Mengidentifikasi Kepribadian Seseorang Menggunakan Support Vector Machine (SVM),” Journal of Informatics and Technology, Vol 2, No 3, pp. 125-133, 2013.

I. Awaludin och A. Khairunisa, ”Aplikasi Grafologi dari Huruf "t" Menggunakan Jaringan Syaraf Tiruan,” Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI) UGM, Vol.4, No.3, 2015.

P. Joshi, A. Agarwal, A. Dhavale och S. Kodolikar, ”Handwriting Analysis for Detection of Personality Traits using Machine Learning Approach,” International Journal of Computer Applications (0975-8887), Volume 130, No.15, 2015.

S. Dwikardana, Practical Handbook of Graphology, Yogyakarta: Penerbit PT Kanisius, 2014.

W. Setyaningsih, Mengenal Kepribadian Lewat Tulisan, Yogyakarta: NOTEBOOK, 2015.

R. A. Noe, J. R. Hollenbeck, B. Gerhart och P. M. Wright, Manajemen Sumber Daya Manusia : Mencapai Keunggulan Bersaing, Jakarta: Penerbit Salemba Empat, 2010.

R. C. Gonzales och R. E. Woods, Digital Image Processing, New Jersey: Pearson Prentice Hall, 2010.

T. Sutojo, E. Mulyanto och V. Suhartono, Kecerdasan Buatan, Yogyakarta: Penerbit ANDI, 2011.

Suyanto, Artificial Intelligence, Bandung: Penerbit Informatika, 2014.

J. Amezcua, P. Melin och O. Castillo, ”A Neural Network with a Learning Vector Quantization Algorithm for Multiclass Classification Using a Modular Approach,” Recent Developments and New Direction in Soft-Computing Foundations and Applications, Springer, Cham, 2016, pp. 171-184.




DOI: http://dx.doi.org/10.22146/jnteti.v6i3.340

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