IMPLEMENTASI K-MEANS CLUSTERING PADA TERJEMAHAN AL-QUR’AN BERDASARKAN KETERKAITAN TOPIK

The clustering process can perform grouping of data, so data which have high simmilarity will be grouped into the same cluster. One of the most commonly used clustering algorithms is K-Means. Grouping related paragraph will allow the user to find a theme in the Qur’an. This study aims to see the accuracy of the K-Means algorithm for clustering the verses of the Qur’an This research was conducted with pre-processing text of Qur’an verse, term-weighting with TF-IDF, normalize using cosine normalization, and then clustering using K-Means algorithm. Based on the test result using K-Means algorithm successfully perform clustering on Al-Baqarah verses with accuracy of 43%. To increase the value of testing required centroid selection algorithms for initial values, reduction of data dimensions, and algoritms for distance measurement and similiarity