Analisis Fitur Pada Citra Gestur Tangan Sistem Isyarat Bahasa Indonesia
DOI:
https://doi.org/10.22441/format.2023.v12.i2.010Kata Kunci:
pengenalan gestur tangan, ekstraksi fitur, SIBI, WEKAAbstrak
Implementasi pengenalan gestur tangan telah banyak digunakan pada interaksi manusia dan komputer dekade terakhir ini. Implementasi pengenalan gestur tangan dapat meliputi banyak bidang, mulai dari bidang hiburan hingga bidang kesehatan atau medis. Untuk menghasilkan pengenalan gestur tangan yang baik, tentunya dibutuhkan penggunaan fitur yang tepat. Penelitian ini bertujuan menganalisis fitur dari citra statik gestur tangan agar dapat diimplemetasikan pada perangkat gawai tanpa menggunakan perangkat khusus. Pada penelitian sebelumnya fitur yang digunakan pada pengenalan gestur tangan berupa arah jari, panjang jari, posisi sendi, jarak ujung jari terhadap telapak tangan, sudut antar sendi-sendi jari berdekatan, serta sudut antara telapak tangan, pangkal jari, dan ujung jari. Berdasarkan penelitian terdahulu tersebut, diusulkan metode adalah dengan menggunakan fitur jarak, sudut, dan kuadran. Dataset yang digunakan berupa 528 data citra gestur tangan alfabet SIBI. Pengujian dilakukan dengan perangkat lunak WEKA menggunakan algoritme Naive Bayes, K-Nearest Neighbor(KNN), Neural Network, Support-Vector Machine (SVM), dan C4.5. Algoritme-algoritme tersebut dipilih karena dinilai memiliki karakteristik serta kebutuhan dataset yang berbeda sehingga pengujian fitur yang diusulkan dapat dilakukan secara menyeluruh. Metode K-fold cross validation digunakan pada pengujian untuk mengetahui akurasi terbaik. Hasil yang didapat adalah gabungan dari fitur jarak, sudut, dan kuadran dinilai palin baik diterapkan dengan akurasi tertinggi sebesar 60%.
Unduhan
Referensi
J. Zhao and R. S. Allison, “Comparing head gesture, hand gesture and gamepad interfaces for answering Yes/No questions in virtual environments,” Virtual Real., vol. 24, no. 3, 2020.
Y. Cho, A. Lee, J. Park, B. Ko, and N. Kim, “Enhancement of gesture recognition for contactless interface using a personalized classifier in the operating room,” Comput. Methods Programs Biomed., vol. 161, 2018.
Ridwang, Syafaruddin, A. A. Ilham, and I. Nurtanio, “Indonesian Sign Language Letter Interpreter Application Using Leap Motion Control based on Naïve Bayes Classifier,” in IOP Conference Series: Materials Science and Engineering, 2019, vol. 676, no. 1.
Y. Liu, L. Zhang, and S. Zhang, “A hand gesture recognition method based on multi-feature fusion and template matching,” in Procedia Engineering, 2012, vol. 29.
T. D. Pangestuti, F. T. Anggraeny, and E. P. Mandyartha, “Rancang Bangun Sistem Pendukung Keputusan Penerimaan Karyawan Baru Menggunakan Metode Naive Bayes Classifier (Studi Kasus PT. Sasmito),” J. Inform. dan Sist. Inf., vol. 1, no. 3, 2020.
M. Rifki and I. Imelda, “ANALISIS SENTIMEN WACANA KENAIKAN HARGA TIKET CANDI BOROBUDUR MENGGUNAKAN MULTINOMIAL NAÏVE BAYES,” JIKO (Jurnal Inform. dan Komputer), vol. 5, no. 2, pp. 156–163, 2022.
Z. E. Sholikha, E. Y. Puspaningrum, and W. S. J. Saputra, “Analisa Sentimen Pengguna E-Money pada Twitter Menggunakan Algoritma C4.5 dan Naïve Bayes,” J. Inform. dan Sist. Inf., vol. 1, no. 3, pp. 1063–1071, 2020.
I. K. Wiratama, Welda, I. P. H. Permana, M. D. W. Aristana, and I. G. I. Sudipa, “RECOMMENDATION FOR HIGH SCHOOL DETERMINATION BASED ON ACADEMIC POTENTIAL USING NAÏVE BAYES METHOD,” JIKO (Jurnal Inform. dan Komputer), vol. 5, no. 2, pp. 108–117, 2022.
E. Y. Puspaningrum, B. Nugroho, and D. P. Safira, “Implementation Of K-Nearest Neighbor - Certainty Factor For Expert System Detection Of Idiopathic Thrombocytopenic Purpura,” E3S Web Conf., vol. 328, 2021.
F. R. Irawan, A. Jazuli, and T. Khotimah, “Analisis Sentimen Terhadap Pengguna Gojek Menggunakan Metode K-Nearset Neighbors,” JIKO (Jurnal Inform. dan Komputer), vol. 5, no. 1, pp. 62–68, 2022.
A. H. Baksir, A. Fuad, F. Tempola, and R. Rosihan, “Prediksi Tingkat Kesuburan (Fertility) dengan Jaringan Saraf Tiruan Metode Backpropagation,” JIKO (Jurnal Inform. dan Komputer), vol. 3, no. 2, pp. 107–112, 2020.
N. Nurhanudin and J. E. Riwurohi, “Prediksi Jumlah Pendaftar Haji Lanjut Usia Menggunakan Jaringan Syaraf Tiruan Backpropagation,” JIKO (Jurnal Inform. dan Komputer), vol. 4, no. 2, pp. 112–121, 2021.
D. Tuhenay and E. Mailoa, “Perbandingan Klasifikasi Bahasa Menggunakan Metode Naïve Bayes Classifier (NBC) Dan Support Vector Machine (SVM),” JIKO (Jurnal Inform. dan Komputer), vol. 4, no. 2, pp. 105–111, 2021.
S. Bhushan, M. Alshehri, I. Keshta, A. K. Chakraverti, J. Rajpurohit, and A. Abugabah, “An Experimental Analysis of Various Machine Learning Algorithms for Hand Gesture Recognition,” Electron., vol. 11, no. 6, 2022.
M. Abrori, “Hand Gesture Dataset,” Kaggle, 2022. [Online]. Available: https://www.kaggle.com/datasets/merdinabrori/hand-gesture-dataset. [Accessed: 29-Nov-2022].
X. Zhang, W. Xie, S. Li, and X. Liu, “Convolutional Neural Networks Based Motion Data Optimization Networks for Leap Motion,” Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal Comput. Des. Comput. Graph., vol. 33, no. 3, 2021.
Unduhan
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
The copyright to this article is transferred to Universitas Mercu Buana (UMB) if and when the article is accepted for publication. The undersigned hereby transfers any and all rights in and to the paper including without limitation all copyrights to UMB. The undersigned hereby represents and warrants that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required. The undersigned represents that he/she has the power and authority to make and execute this assignment.
We declare that this paper has not been published in the same form elsewhere.
Furthermore, I/We hereby transfer the unlimited rights of publication of the above-mentioned paper as a whole to UMB. The copyright transfer covers the right to reproduce and distribute the article, including reprints, translations, photographic reproductions, microform, electronic form (offline, online) or any other reproductions of similar nature.
The corresponding author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors. This agreement is to be signed by at least one of the authors who have obtained the assent of the co-author(s) where applicable. After submission of this agreement signed by the corresponding author, changes of authorship or in the order of the authors listed will not be accepted.
Retained Rights/Terms and Conditions
Although authors are permitted to re-use all or portions of the Work in other works, this does not include granting third-party requests for reprinting, republishing, or other types of re-use.
Our Articles are licensed under CC BY-NC
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
