Analisis Performa Metode Gaussian Naïve Bayes untuk Klasifikasi Citra Tulisan Tangan Karakter Arab
Abstract
Berdasarkan penelitian yang dilakukan oleh Herman dkk., peneliti mencoba mengangkat kembali metode yang diterapkan dengan menggunakan dataset yang berbeda dan dengan jumlah yang lebih banyak. Penelitian ini bertujuan untuk menghitung performa metode (akurasi, presisi, recall, dan f-measure) Gaussian Naïve Bayes. Dataset yang digunakan adalah citra tulisan tangan karakter arab. Berdasarkan hasil perhitungan performa menunjukkan tingkat akurasi tertinggi sebesar 12%, presisi 10%, recall 12%, dan f-measure 8%.
Downloads
References
R. Akbar and E. A. Sarwoko, “Studi Analisis Pengenalan Pola Tulisan Tangan Angka Arabic (Indian) Menggunakan Metode K-Nearest Neighbors dan Connected Component Labeling,” vol. 12, no. 2, pp. 45–51, 2016.
A. Zahriyono, A. Suryan, and M. D. Suliiyo, “Implementasi Pembacaan Huruf Hijaiyyah Dan Karakter Angka Arab Dengan Menggunakan Jaringan Syaraf Tiruan LVQ (Learning Vector Quantization),” Universitas Telkom, 2013.
A. El-Sawy, M. Loey, and H. El-Bakry, “Arabic Handwritten Characters Recognition using Convolutional Neural Network,” 2019 10th Int. Conf. Inf. Commun. Syst. ICICS 2019, vol. 5, pp. 147–151, 2017, doi: 10.1109/IACS.2019.8809122.
R. D. Nurfita and G. Ariyanto, “Implementasi Deep Learning Berbasis Tensorflow untuk Pengenalan Sidik Jari,” Emit. J. Tek. Elektro, vol. 18, no. 01, pp. 22–27, 2018, doi: 10.23917/emitor.v18i01.6236.
Herman et al., “Comparison of Artificial Neural Network and Gaussian Naïve Bayes in Recognition of Hand-Writing Number,” Proc. - 2nd East Indones. Conf. Comput. Inf. Technol. Internet Things Ind. EIConCIT 2018, no. 1, pp. 276–279, 2018, doi: 10.1109/EIConCIT.2018.8878651.
H. Kamel, D. Abdulah, and J. M. Al-Tuwaijari, “Cancer Classification Using Gaussian Naive Bayes Algorithm,” Proc. 5th Int. Eng. Conf. IEC 2019, pp. 165–170, 2019, doi: 10.1109/IEC47844.2019.8950650.
Y. Mardi, “Data Mining : Klasifikasi Menggunakan Algoritma C4.5,” J. Edik Inform., vol. 2, no. 2, pp. 213–219, 2017.
R. Yanto and R. Khoiriah, “Implementasi Data Mining dengan Metode Algoritma Apriori dalam Menentukan Pola Pembelian Obat,” Creat. Inf. Technol. J., vol. 2, no. 2, pp. 102–113, 2015, doi: 10.24076/citec.2015v2i2.41.
G. Kesavaraj and S. Sukumaran, “A Study On Classification Techniques in Data Mining,” 2013.
N. A. Haryono, W. Hapsari, A. Angesti, and S. Felixiana, “Penggunaan Momen Invariant, Eccentricity, Dan Compactness Untuk Klasifikasi Motif Batik Dengan K-Nearest Neighbour,” J. Inform., vol. 11, no. 2, pp. 107–115, 2016, doi: 10.21460/inf.2015.112.411.
F. Tempola, M. Muhammad, and A. Khairan, “Perbandingan Klasifikasi Antara KNN dan Naive Bayes pada Penentuan Status Gunung Berapi dengan K-Fold Cross Validation,” J. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 5, p. 577, 2018, doi: 10.25126/jtiik.201855983.
C. A. Sugianto, “Penerapan Teknik Data Mining Untuk Menentukan Hasil Seleksi Masuk SMAN 1 Gibeber Untuk Siswa Baru Menggunakan Decision Tree,” J. TEDC, vol. 9, no. 1, pp. 39–43, 2015, doi: 10.31227/osf.io/vedu7.
Copyright (c) 2022 Indonesian Journal of Data and Science
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal.
- The work is not under consideration for publication elsewhere.
- The work has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with Indonesian Journal of Data and Science 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-NonCommercial 4.0 International License. (CC BY-NC 4.0) 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.