JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Vol. 9 No. 4 (2025): August 2025

Detection of Qur’anic Ikhfa Patterns in Digital Images Using Binary Similarity Distance Measures (BSDM) with 3W-Jaccard Formula

Julianansa, Ririn (Unknown)
Fadlisyah (Unknown)
Yesy Afrillia (Unknown)



Article Info

Publish Date
03 Aug 2025

Abstract

Recitation rules in the Qur'anic script form various visual patterns. One of the selected rules for this study is the Ikhfa pattern. Ikhfa is a recitation rule pronounced subtly when the nun sukun (نْ) or tanwin (ـَــًـ, ـِــٍـ, ـُــٌـ) is followed by one of 15 specific letters, namely: ta’ (ت), tsa’ (ث), jim (ج), dal (د), dzal (ذ), za’ (ز), sin (س), syin (ش), shad (ص), dhad (ض), tha’ (ط), zha’ (ظ), fa’ (ف), qaf (ق), and kaf (ك). In this study, the primary challenge is the difficulty of automatically detecting the Ikhfa pattern in both digital and printed Qur'anic texts. This challenge arises from the subtlety of the recitation rule, which makes it difficult to distinguish from other recitation patterns. To address this, the Ikhfa pattern is detected using image processing techniques, and pattern classification is performed using the Binary Similarity and Distance Measures (BSDM) method. The results indicate that the pattern detection system, employing BSDM with the 3W-Jaccard formula, achieved a detection rate of 83.84%. This suggests that the 3W-Jaccard formula is an effective approach for detecting similar recitation patterns. One advantage of the 3W-Jaccard formula is its ability to recognize patterns with a relatively small amount of reference data, making it highly suitable for implementation in the detection system.

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Journal Info

Abbrev

JAIC

Publisher

Subject

Computer Science & IT

Description

Journal of Applied Informatics and Computing (JAIC) Volume 2, Nomor 1, Juli 2018. Berisi tulisan yang diangkat dari hasil penelitian di bidang Teknologi Informatika dan Komputer Terapan dengan e-ISSN: 2548-9828. Terdapat 3 artikel yang telah ditelaah secara substansial oleh tim editorial dan ...