Optimizing Qur'an Recitation Monitoring with Random Forest Algorithm
DOI:
https://doi.org/10.15575/kjrt.v2i1.227Keywords:
Classification, Machine Learning, Random Forest, Reciting Al-Qur’anAbstract
Every Muslim should improve their worship, including reciting the Al-Qur'an. Reciting the Al-Qur'an is a deep spiritual practice that provides spiritual benefits and blessings daily. To maximize the benefits of reciting Al-Qur'an during this holy month, implementing Machine Learning can make a significant contribution. This research explores the application of Machine Learning using the Random Forest algorithm to improve the practice of reciting the Al-Qur'an. By collecting data through surveys using questionnaires, this research identifies important factors that influence an individual's success in completing reading the Al-Qur'an. The research results show that the Random Forest algorithm can be used to predict the number of individuals who have the potential to complete reciting Al-Qur'an with an accuracy value of 80%.
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