<![CDATA[Memorizing the Qur’an is a highly recommended act of worship for Muslims, yet traditional learning methods often face constraints such as limited availability of competent teachers. With technological advancements, innovations to support the memorization process independently, objectively, and efficiently are greatly needed. This research aims to develop and measure the performance of an automated system for testing the memorization of Surat Al-Ghasyiyah (verses 1–26) through voice recognition using the Walsh Transform method. The Walsh Transform is applied to convert voice signals from the time domain to the frequency domain using basis functions valued at +1 and −1, extracting unique features from each verse to be compared with reference voice samples. The system was tested on all 26 verses using 6 training voice samples and 4 test voice samples per verse (total 260 samples: 156 training and 104 test). System performance was evaluated using four variations of probability constants: 0.3, 0.4, 0.5, and 0.6. Results indicate that the probability constant significantly affects system accuracy. Detection rates achieved were 70.2% (constant 0.3), 84.6% (constant 0.4), 89.4% (constant 0.5), and peaked at 93.3% (constant 0.6). With an overall average detection rate of 84.4%, it is concluded that the Walsh Transform method is highly effective and the developed system has potential as a reliable aid for Qur’an memorizers.]]>
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