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All Journal Jurnal Ilmu Komputer dan Agri-Informatika
Eylen Desy Novita
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Agriculture, Biological Sciences & Forestry Computer Science & IT

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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 Vol 9 No 1 (2022)
Publisher : Departemen Ilmu Komputer, Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jika.9.1.58-69

Abstract

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%.
Co-Authors Anuraga Jayanegara Aziz Kustiyo Hari Agung Adrianto Toto Haryanto