Learning Vector Quantization Image for Identification Adenium

Abstract

Information and technology are two things that can not be separated and it has become a necessity for human life. Technology development at this time was not only used for intelligence purposes only, but has penetrated the world of holtikurtura. Adenium is one of the plants are much favored by ornamental plants lovers. Many of cultivation adenium who crosses that appear new varieties that have the color and shape are similar to each other. From this case, then made an application that can identify the type of adenium based on the image of that flower. Learning Vector quantization is one of the algorithm  that used for clustering. Based on test scenarios were performed, image identification applications Adenium petals produce an accuracy of 86.66% with a number of training dataset of 135 images and datasets with a test as many as 45 images max epoch 10 and learning rate between 0.01 to 0.05.