Personality Analysis through Handwriting Detection Using Android Based Mobile Device
DOI:
https://doi.org/10.25126/jitecs.20172237Abstract
Graphology is one of the psychology disciplines which aims to study the personality traits of individuals through interpretation of handwriting. We can get information of one’s personality through graphology. In addition, by using android based mobile device, graphology analysis could show one’s personality faster. This study was conducted by taking 42 samples of handwriting from different backgrounds. The feature used in this study was handwriting margin. Besides, Support Vector Machine method was employed to classify the result feature from extraction process. The result of this study showed the accurate average of the application reached 82.738%.References
Arridho, G. K., Endah, S. U, Sugiharto, A. 2013. Analisis Pen Pressure Tulisan Tangan untuk Mengidentifikasi Kepribadian Seseorang Menggunakan Support Vector Machine (SVM). Journal of Informatics and Technology Vol 2 No 3 (66 – 76).
Gazali, W., Nilo L., Harry T. S. 2013. Aplikasi Pengenalan Tulisan Tangan untuk Ekspresi Matematika Berbasiskan Komputer. Jurnal Mat Stat Vol 13 No 2 (85 – 90).
Hermawati, Astuti, F. 2013. Pengolahan Citra Digital Konsep & Teori. Yogyakarta: ANDI Offset.
Hsu, C.W. dan Lin, C.J. 2002. A Comparison of Methods for Multi-class Support Vector Machines. IEEE Transaction on Neural Network, 13(2) : 415-425.
Novianti, F.A dan Purnami, S.W. 2012. Analisis Diagnosis Pasien Kanker Payudara Menggunakan Regresi Logistik dan Support Vector Machine (SVM) Berdasarkan Hasil Mamografi. Jurnal Sains dan Seni ITS, Vol. 1, No. 1 ISSN : 2301-928X.
Nugroho, K. 2013. 1 Jam Belajar Grafologi: Cara Mudah Menganalisis Tulisan Tangan. Semarang: Effhar Offset.
Prasetiawan, E., Sugiharto, A., Endah, S. N. 2013. Analisis Pola Garis Tulisan Tangan untuk Mengidentifikasi Kepribadian Seseorang Menggunakan Support Vector Machine (SVM). Journal of Informatics and Technology Vol 2 No 3 (125 – 133).
Prasetyono, D.S. 2010. Bedah Lengkap Grafologi. Yogyakarta: Diva Press.
Putra, D. 2010. Pengolahan Citra Digital. Jogjakarta: Andi.
Rachman, F dan Purnami, S.W. 2012. Klasifikasi Tingkat Keganasan Breast Cancer dengan Menggunakan Regresi Logistik Ordinal dan Support Vector Machine (SVM). Jurnal Sains dan Seni ITS, Vol. 1, No. 1 ISSN : 2301-928X.
San, Y. S. 2016. Graphology for Recruitment. Yogyakarta: Psikologi Corner.
Santosa, B. 2007. Data Mining Teknik Pemanfaatan Data untuk Keperluan Bisnis. Graha Ilmu : Yogyakarta.
Sutoyo, T., Mulyanto, E., dkk. 2009. Teori Pengolahan Citra Digital. Yogyakarta: ANDI Offset.
Vapnik, V dan Cortes, C. 1995. Support Vector Networks. Machine Learning, 20, 273-297.
https://www.idc.com/promo/smartphone-market-share/os. Selasa, 1 Agustus 2017. Pk 15.00WIB.
Rohwana, Ulir dan Irawan, M. Isa. 2013. Pengenalan Tulisan Tangan Huruf Latin Bersambung Secara Real Time Menggunakan Algoritma Learning Vector Quantization. Jurnal Sains dan Seni Pomits Vol. 2, No 1.
Ahmad, Khalid, M., Viard-Gaudin, A.R. 2009. Lexicon-based Word Recognition Using Support Vector Machine and Hidden Markov Model. International Conference on Document Analysis and Recognition.
Widoretno, Sri, Sarosa, M., Muslim, Muhammad Aziz. 2013. Implementasi Pengenalan Karakter Seseorang Berdasarkan Pola Tulisan Tangan. Jurnal EECCIS Vol. 7, No. 2, Desember 2013.
Downloads
Published
How to Cite
Issue
Section
License
 Creative Common Attribution-ShareAlike 3.0 International (CC BY-SA 3.0)
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).