PENERAPAN METODE ANALISIS DISKRIMINAN DALAM MENGELOMPOKKAN JENIS KALENG BERDASARKAN CITRA RGB
Daftar Isi:
- Tin waste cans have properties that are difficult to decompose on the ground causing adverse impacts. To reduce the waste waste cans can be recycled. The first stage in recycling cans be to group them according to certain criteria. In this study will be grouped canned type based on Red Green Blue Image (RGB). The data used consisted of training data and test data with 250 samples. In the data train and test data used several factors of the image cans. Factors used are four angle lights and two light bulbs and two speeds of moving boards as a group. This study aims to determine the discriminant function and the level of accuracy obtained from the grouping results. This study uses the Principal Component Analysis method (PCA) to reduce the free variables used in the training data and test data and use the Randomized Block Design (RBD) method to see the biggest factor influences. The grouping method used is the Discriminant Analysis method. In this research, grouping is done on training data and test data of free variable reduction as well as on training data and original test data without free variable reductions. The discriminant function formed is a quadratic discriminant function. The greatest accuracy level was obtained on the train data, and test data factors type of speed of board 2 lamp 1 angle of lighting 90° with the result of 52,4%. This indicates that the quadratic discriminant function is formed well enough in grouping the type of cans.