TY  - THES
N1  - M. Didik Rohmad Wahyudi, ST., MT
ID  - digilib31679
UR  - https://digilib.uin-suka.ac.id/id/eprint/31679/
A1  - AHMAD SALAM WAHID FAIZIN, NIM. 12650026
Y1  - 2018/06/23/
N2  - 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.
PB  - UIN SUNAN KALIJAGA YOGYAKARTA
KW  - Clustering
KW  -  K-Means Clustering
KW  -  Al-Qur?an
KW  -  Text Mining
M1  - skripsi
TI  - IMPLEMENTASI K-MEANS CLUSTERING PADA TERJEMAHAN AL-QUR?AN BERDASARKAN KETERKAITAN TOPIK
AV  - restricted
ER  -