@thesis{thesis,
		author={NADIA TASZA  and Rifkie },
		title ={KLASIFIKASI MOTIF KAIN BATIK MENGGUNAKAN ALGORITMA NAIVE BAYES CLASSIFIER (NBC) DAN DETEKSI TEPI SOBEL},
		year={2018},
		url={https://repository.unsri.ac.id/10036/},
		abstract={Batik requires classification to help in classifying and distinguishing motifs in Indonesia. One of the good techniques in classifying is Naive Bayes Classifier (NBC). Bayesian Classifier has the possibility of high accuracy and speed if applied to large databases. In this study a classification software was developed using the NBC algorithm which classifies Batik motifs into 4 classes, namely Semen, Lunglungan, Ceplok, and Parang. In this case, several methods are included in the classification efforts, including: Sobel algorithm and United Moment Invariants (UMI). The results showed that the software was able to classify motifs with an accuracy rate of 52.50% from the test results using 120 Batik images.}
		}