Aplikasi Grafologi dari Huruf “t” Menggunakan Jaringan Syaraf Tiruan

  • Iwan Awaludin Politeknik Negeri Bandung
  • Aulia Khairunisa Universitas Komputer Indonesia
Keywords: grafologi, jaringan syaraf tiruan, levenberg marquadt

Abstract

Graphology is a branch of science which classifies human personality from handwriting. Graphologists observe the patterns of handwriting and compare it with personality class database. Computers can be trained to do the same procedure of human personality classification based on handwriting. The procedure is to perform digital image processing that extracts features from handwriting images. The features will become input for Artificial Neural Network. Neural networks that are already configured with a number of hidden layers, the number of neurons, activation function, and the particular learning algorithm will be able to recognize certain classes of human handwriting, thus his personality. Tested configurations include: changing the number of neurons in the hidden layer of eight to twelve, binary image resizing, changing the activation function, and also changing the learning algorithm. Results of simulation and analysis are also provided.

References

B. Lutfianto, Analisis Tulisan Tangan: Grapho for Succ. Gramedia Pustaka Utama, 2011.

F. Widiastuti, W. Kaswidjanti, and H. C. Rustamaji, “JARINGAN SARAF TIRUAN BACKPROPAGATION UNTUK APLIKASI PENGENALAN TANDA TANGAN,” Telematika, vol. 11, no. 1, 2015.

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H. N. Champa and K. R. AnandaKumar, “Artificial Neural Network for Human Behavior Prediction through Handwriting Analysis,” Int. J. Comput. Appl. IJCA, vol. 2, no. 2, pp. 36–41, 2010.

M. Grundland and N. A. Dodgson, “The decolorize algorithm for contrast enhancing, color to grayscale conversion,” University of Cambridge, Technical Report UCAM-CL-TR-649, 2005.

How to Cite
Iwan Awaludin, & Aulia Khairunisa. (1). Aplikasi Grafologi dari Huruf “t” Menggunakan Jaringan Syaraf Tiruan. Jurnal Nasional Teknik Elektro Dan Teknologi Informasi, 4(3), 172-176. Retrieved from https://dev.journal.ugm.ac.id/v3/JNTETI/article/view/2997
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Articles