Qur'an verses search applications have been developed over time due to the significance of Qur'an itself which contains information for the Muslims to be used as a guideline for life. The existence of Qur'an verses search applications can ease Muslims in finding the relevant verse in accordance with the query entered. One of the existing applications is Cari Ayat. Despite having existed for quite some time, however, there still a drawback on its search feature where it cannot display the verses that are relevant to the query when users enter more than two words, making this application system lacks in performance when displaying the relevant verse. In addressing this issue, this research uses the term of weighing and distance metrics. The process begins with carrying out pre-processing of the text after which weighing will be performed into the terms resulting from pre-processing by using the TF-RF and Bray-Curtis distance to measure the distance between the document and the query. As many as 50 query used in the testing process. The test results of k-rank value variety indicate that k-rank 5 produces the best MAP value up to 60.36%, which is higher than those of k-rank 10, 15 and 20. The test results achieved by performing the dataset in which the process of cleaning, weighting term TF-RF, and Bray-Curtis distance has been carried out beforehand, may slightly increase the MAP value on the k-rank 5 by 61.80%. Furthermore, the test results using the Kappa Statistic based on the agreement of the two experts, account the value of kappa by 0.8774 which is considered as almost perfect. Based on these results, it can be inferred that TF-RF and Bray-Curtis distance can be utilized to find the relevant texts in the translation of Qur'an verse.