Aplikasi Pengenalan Nama Surah pada Juz ke 30 Kitab Suci Al-Qur’an Menggunakan Speech Recognition

  • Dhimas Sena Rahmantara Politeknik Caltex Riau
  • Kartina Diah Kesuma Wardhani Politeknik Caltex Riau
  • Maksum Ro’is Adin Saf Politeknik Caltex Riau
##plugins.pubIds.doi.readerDisplayName##: https://doi.org/10.29207/resti.v2i1.285
Keywords: Al-Qur’an, Juz 30th, Markov Model, Speech Recognition.

Abstract

Al-Quran is a scripture which contains the saying of Allah Subhanahu Wa Taaala and was revealed to Prophet Muhammad. The 30th juz is the juz that exists in the Al-Quran. When studying how to read Al-Quran well, the first thing that is learned is reading and memorizing surahs in the 30th juz. Nevertheless, there is a problem in remembering or knowing the surah name and the verse which are in the 30th juz. An android application was developed in order to recognize the surah names in the 30th juz by utilizing speech recognition technology to overcome that problem. Markov Model (Markov Chain) algorithm was implemented in this application. This algorithm will process users speech and compute probability of the surah name that was spoken. Speech detection testing gave result that the highest accuracy of application in recognizing the speeches was in the environment without noise with the accuracy of 100% in the most ideal distance is 50 cm for male and for female user. Based on the blackbox testing result, all functionalities of the application have functionated well. Control flow testing gave result that the value is 7 which indicates that the code is simple and well written. 87,74% respondents answered, by filling up the questionnaires, that the application is useful in order to make user knows better about the surah names in the 30th juz.

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References

[1] P. Christensson, "Speech Recognition," 2014. [Online].Available: https://techterms.com/definition/speech_recognition. [Accessed 23 April 2017].
[2] A. W. Dani, "Perancangan Aplikasi Voice Command Recognition Berbasis Android dan Arduino Uno," Jurnal Teknologi Elektro Universitas Mercu Buana, pp. Volume 1, No 1, Halaman 11-19, 2016.
[3] A. A. Zuhdi, "Upaya Pengingkatan Kemampuan Menghafal Juz ‘Amma Melalui Metode Jama’ Siswa Kelas IV SDIT Al-Ma’ruf Tegalrejo Magelang," Sekolah Tinggi Agama Islam Negeri Salatiga, Salatiga, 2011.
[4] D. Natalia, "Perancangan dan Implementasi Speech Recognition Sistem sebagai Fungsi Unlock pada Handset Android," Universitas Telkom, Bandung, 2013.
[5] T. Porwasih, "Aplikasi Speech To Text Pada Animasi Robot Pintar Berbasis Android," Jurnal Aksara Komputer Terapan Politeknik Caltex Riau, pp. Volume 2, No 2, Halaman 209-215, 2013.
[6] F. P. Putra, "Aplikasi Kontrol Slide Microsoft Office Powerpoint Dengan Suara Menggunakan Teknologi Windows Speech Recognition," Jurnal Aksara Komputer Terapan Politeknik Caltex Riau, pp. Volume 3, No 1, Halaman 96-103, 2014.
[7] M. Hasbi, "Speech Recognition Menggunakan Algoritma Markov Model Untuk Mengontrol Lampu," Jurnal Aksara Komputer Terapan Politeknik Caltex Riau, pp. Volume 5, No 1, Halaman 376-384, 2016.
[8] Kemdikbud (Pusat Bahasa), "Alquran," 2017. [Online]. Available: http://kbbi.web.id/Alquran. [Accessed 24 April 2017].
[9] A. Noertjahyana and R. Adipranata, "Implementasi Sistem Pengenalan Suara Menggunakan SAPI 5.1 dan Delphi 5," Jurnal Informatika Universitas Petra, pp. Volume 4, No 2, Halaman 107-114, 2003.
[10] Y. Supardi, Semua Bisa Menjadi Programmer Android, Jakarta: PT Elex Media Komputindo, 2014.
[11] M. I. Mas’ud, "Pendekatan Rantai Markov Dalam Pemilihan Universitas di Pasuruan," Journal Knowledge Industrial Engineering (JKIE) Universitas Yudharta, pp. Volume 4, No 1, Halaman 63-70, 2017.
[12] E. Abdurachman, "Konsep Dasar Markov Chain Serta Kemungkinan Penerapannya di Bidang Pertanian," Jurnal Informatika Pertanian, pp. Volume 8, Halaman 499-505, 1999.
[13] Sekaran, Uma & Bougie, Roger, Research Methods for Business, Chichester: John Wiley & Sons Ltd, 2009.
Published
2018-04-17
Section
Technology Information Article