Pengenalan Suara Dzikir Menggunakan Ekstraksi Fitur MFCC dan Support Vector Machine
DOI:
https://doi.org/10.29407/5b6hrr71Keywords:
Pengenalan Suara, MFCC, Support Vector Machine, dzikir, Klasifikasi SuaraAbstract
Dzikir merupakan aktivitas ibadah yang dilakukan secara lisan dan memiliki variasi pelafalan antarindividu. Perbedaan intonasi, tempo, dan karakteristik suara tersebut dapat menyulitkan sistem komputer dalam mengenali jenis bacaan dzikir secara otomatis. Penelitian ini bertujuan untuk membangun sistem pengenalan suara dzikir dengan memanfaatkan metode ekstraksi fitur Mel-Frequency Cepstral Coefficients (MFCC) dan algoritma klasifikasi Support Vector Machine (SVM). MFCC digunakan untuk merepresentasikan karakteristik sinyal suara dalam domain frekuensi yang mendekati persepsi pendengaran manusia, sedangkan SVM diterapkan untuk melakukan proses klasifikasi berdasarkan fitur yang dihasilkan. Dataset berupa rekaman suara dzikir dikumpulkan dan diproses melalui tahapan pra-pemrosesan, ekstraksi fitur, pelatihan, serta pengujian model. Hasil pengujian menunjukkan bahwa kombinasi MFCC dan SVM mampu mengenali suara dzikir dengan tingkat akurasi yang baik dan stabil. Penelitian ini diharapkan dapat menjadi dasar dalam pengembangan aplikasi pembelajaran dan evaluasi bacaan dzikir berbasis pengenalan suara secara otomatis.
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[1] L. R. Rabiner and B. H. Juang, Fundamentals of Speech Recognition. in Prentice-Hall Signal Processing Series: Advanced monographs. PTR Prentice Hall, 1993. [Online]. Available: https://books.google.co.id/books?id=XEVqQgAACAAJ
[2] S. Davis and P. Mermelstein, “Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences,” IEEE Trans Acoust, vol. 28, no. 4, pp. 357–366, 1980, doi: 10.1109/TASSP.1980.1163420.
[3] T. F. Quatieri, Discrete-time Speech Signal Processing: Principles and Practice. in Pearson Education signal processing series. Prentice Hall PTR, 2002. [Online]. Available: https://books.google.co.id/books?id=5KYeAQAAIAAJ
[4] X. Huang, A. Acero, and H.-W. Hon, Spoken language processing : a guide to theory, algorithm, and system development. New Jersey, United States: Upper Saddle River, NJ : Prentice Hall PTR, 2001. [Online]. Available: https://searchworks.stanford.edu/view/4683582
[5] R. Rosdiana, M. Ula, and H. A. K. Aidilof, “Implementasi Pemodelan Citra Model Svm (Support Vector Machine) Dalam Penentuan Pengklasifikasian Jenis Suara Kontes Burung,” Jurnal Informatika Kaputama (JIK), vol. 5, no. 2, pp. 317–324, 2021.
[6] Md. Sahidullah and G. Saha, “Design, analysis and experimental evaluation of block based transformation in MFCC computation for speaker recognition,” Speech Commun, vol. 54, no. 4, pp. 543–565, 2012, doi: https://doi.org/10.1016/j.specom.2011.11.004.
[7] I. P. S. Sari, A. Fadlil, and T. Sutikno, “Islamic Sound Recognition Using MFCC and SVM: Case Study on Takbir and Sholawat,” Journal of Computer Networks, Architecture and High Performance Computing, vol. 7, no. 3, pp. 825–839, 2025.
[8] J. B and R. Babu.N, Speech recognition using MFCC and DTW. 2014. doi: 10.1109/ICAEE.2014.6838564.
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Copyright (c) 2026 Arie Rahma Nurjannah, Ellok Sintha Maydiana, Patmi Kasih
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