Pengenalan Bahasa Isyarat Indonesia (SIBI) Menggunakan Leap Motion Controller dan Algoritma Data Mining Naïve Bayes

Main Article Content

Ridwang Ridwang

Abstract

Gesture Recognition adalah topik dalam ilmu komputer dan teknologi bahasa dengan tujuan menafsirkan gerakan manusia melalui algoritma matematika. Dalam hal ini dapat digunakan sebagai media penerjemah bagi penyandang tunarungu untuk berkomunikasi. Hambatan utama dari penyandang tunarungu saait ini sulitnya berkomunikasi dengan masyarakat normal, hal itu terjadi karena tidak adanya pembelajaran wajib pada jenjang pendidikan bagi masyarakat normal untuk bahasa isyarat. Metode pada penelitian ini yaitu menggunakan algoritma naive bayesn untuk mengklasifikasikan huruf alfabet bahasa isyarat menggunakan fitur yang berasal dari data Leap Motion Controller.

 

Keywords: Sign Language, Naïve Bayesn, Leap Motion Controller.

Article Details

How to Cite
[1]
R. Ridwang, “Pengenalan Bahasa Isyarat Indonesia (SIBI) Menggunakan Leap Motion Controller dan Algoritma Data Mining Naïve Bayes”, INSYPRO, vol. 2, no. 2, Oct. 2017.
Section
Vol. 2, No. 2

References

[1] L.E. Potter, J. Araullo, L. Carter, Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration, The Leap Motion controller: A view on sign language, Griffith University, Brisbane, Australia, November 25 – 29, 2013; 175-178.
[2] Elons ,A.S. Ahmed, Menna. Shedid, Hwaidaa and Tolba, M.F. Arabic Sign Language Recognition Using Leap Motion Sensor. Industrial Electronics (ISIE), IEEE 23rd International Symposium on. 2014
[3] Chuan, Ching-Hua. Regina, Eric. Guardino, Caroline. American Sign Language Recognition Using Leap Motion Sensor. 2014 13th International Conference on Machine Learning and Applications. 2014
[4] M. Mohandes, S. Aliyu, M. Deriche, International Multi-Conference on Systems, Signals & Devices, Prototype Arabic Sign Language Recognition using Multi-Sensor Data Fusion of Two Leap Motion Controllers, King Fahd University, Saudi Arabia. 2015
[5] Izzah ,Abidatul. Suciati ,Nanik. 2014. Translation Of Sign Language Using Generic Fourier Descriptor And Nearest Neighbour. International Journal on Cybernetics & Informatics ( IJCI) Vol.3, No.1, February 2014.
[6] Supriyati, Endang. Iqbal , Mohammad. Recognition System of Indonesia Sign Language based on Sensor and Artificial Neural Network. Makara Seri Teknologi, 2013; 17(1): 25-31.
[7] G. Marin, F. Dominio, P. Zanuttigh. Hand Gesture Recognition with Leap Motion and Kinect Devices. ), Image Processing (ICIP), 2014 IEEE International Conference on, University of Padova, Italy, 2014:1565-1569
[8] H.Wang, M. Leu, C. Oz, American Sign Language Recognition Using Multi- Dimensional Hidden Markov Models, Journal of Information Science and Engineering 22, 2005:1109-1123
[9] F. Weichert, D. Bachmann, B. Rudak and D. Fisseler, Sensors 13, Analysis of the Accuracy and Robustness of the Leap Motion Controller, Technical University Dortmund, Germany, May 14, 2013:6380-6393
[10] M. Khademi, H. M. Hondori, A. McKenzie, L. Dodakian, C. V. Lopes, S. C. Cramer, CHI ’14 Extended Abstracts on Human Factors in Computing Systems, Freehand interaction with leap motion controller for stroke rehabilitation, University of California, USA, 2014:1663-1668
[11] J. Wachs, M. K¨olsch, H. Stern, Y. Edan, Communications of the ACM Vol 54, No.2, Vision-Based Hand-Gesture Applications, 62-71. 2011
[12] J.Sutton, ACM SIGGRAPH Studio Talks, no. 21, Airpainting with Corel Painter Freestyle and the Leap Motion Controller: A Revolutionary New Way to Paint. 2013
[13] N. Xu, W. Wang, X. Qu, Image and Graphics: 8th International Conference, Recognition of In-Air Handwritten Chinese Character Based on Leap Motion Controller, Tianjin, China, August 13-16. 2015;160-168 35