Prediksi Kandungan Lignin pada Dedak Padi Bercampur Sekam Menggunakan Tekstur Statistik dan KNN - Eylen Desy Novita; Aziz Kustiyo; Anuraga Jayanegara; Toto Haryanto; Hari Agung Adrianto (Jurnal Ilmu Komputer dan Agri-Informatika, 2022)
Adulteration in rice bran happens quite high due to the expensive price of rice bran. Mixing the rice bran with husk could decrease the rice bran quality because the content of crude fiber and lignin cointained in husk are anti-nutrients. Lignin content can be estimated by the texture of rice bran mixed with husk image. This study aimed to analyze the texture of rice bran mixed with husk image using run length feature extraction method with k-nearest neighbour (KNN) classification. The images of rice bran mixed with husk were taken using Dino Capture digital microscope with magnification 200 times. The images were generated with the spatial resolution of 640×480 pixels in a bitmap format. Those images were converted from RGB into grayscale in preprocessing phase, then the result of grayscale images were enhanced using histogram equalization as image enhancement method. The training and testing was determined using 5-fold cross validation with 3 repetition. The result of KNN classification with 7 features showed the highest accuracy of 74.55%.