Keterbatasan waktu orang tua dengan anak dan pengawasan yang dilakukan oleh guru tidaklah dapat menjadi acuan dalam pengawasan ibadah, Selain itu tidak jarang orangtua memiliki kesibukan masing-masing, sehingga pengawasan terhadap anak
menjadi tidak maksimal. Oleh karena itu dibutuhkan sistem monitoring yang dapat memantau ibadah anak yang dapat diakses kapanpun dan dimanapun. Salah satu jenis ibadah yang dapat diverifikasi adalah ibadah membaca Al-QXU¶aQ. UQWXN daSaW memastikan anak telah beribadah diperlukan proses Speech Recognition untuk mengubah suara menjadi teks, dimana hasil ucapan teks akan dicocokkan dengan ayat Al-QXU¶aQ daQ dihiWXQg NePiUiSaQQ\a deQgaQ aOgRUiWPa Cosine Similarity.
Pengujian dilakukan sebanyak 30 kali percobaan membaca ayat Al-QXU¶aQ, hasil tingkat akurasi algoritma Cosine Similarity dengan pembobotan Term FrequencyInvers Document Frequency (TF-IDF) menghasilkan nilai akurasi sebesar 73%, sedangkan menggunakan pembobotan Term Frequency (TF) nilai akurasi yang didapatkan lebih besar, yaitu sebesar 84%.

The limited time between parents and children and the supervision carried out by the teacher cannot be used as a reference in supervising worship. In addition, it is not uncommon for parents to have their respective activities, so that supervision of children is not optimal. Therefore a monitoring system is needed that can monitor children's worship that can be accessed anytime and anywhere. One type of worship that can be verified is the worship of reading the Al-Qur'an. In order to ensure that the child has worshiped, a Speech Recognition process is needed to convert the voice into text, where the results of the spoken text will be matched with the verses of the Qur'an
and the similarity is calculated with the Cosine Similarity algorithm. The test was carried out 30 times in reading the verses of the Koran, the results of the accuracy of the
Cosine Similarity algorithm with the weighting of Term Frequency-Invers Document Frequency (TF-IDF) resulted in an accuracy value of 73%, while using the weighting of Term Frequency (TF) the accuracy value obtained is greater, which is equal to 84%.