Endek Classification Based On GLCM Using Artificial Neural Networks with Adam Optimization - Guna, Putu Wahyu Tirta; Putri, Luh Arida Ayu Ayu Rahning (JELIKU (Jurnal Elektronik Ilmu Komputer Udayana); Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020DO - 10.24843/JLK.2020.v09.i02.p16, 2020)
Not many people know that endek cloth itself has 4 known variances. .Nowadays. Computing and classification algorithm can be implemented to solve classification problem with respect to the features data as input. We can use this computing power to digitalize these endek pattern. The features extraction algorithm used in this research is GLCM. Where these data will act as input for the neural network model later. There is a lot of optimizer algorithm to use in back propagation phase. In this research we  prefer to use adam which is one of the newest and most popular optimizer algorithm. To compare its performace we also use SGD which is older and popular optimizer algorithm. Later we find that adam algorithm generate 33% accuracy which is better than what SGD algorithm give, it is 23% accuracy. Longer epoch also give affect for overall model accuracy.