Fahlawi, Ahmad RezaSalambue, Roni2019-04-302019-04-302019-04-30wahyu sari yenihttps://repository.unri.ac.id/handle/123456789/9672This study was focused to identify the ripeness level of oil palm Fresh Fruit Bunch (FFB) using image processing. Laser Speckle imaging (LSI) is used as an optical method to find out bio-speckle activity. Image acquisition was obtained by laser illuminating the fruit and the light beam of the fruit would be recorded. Digital image feature extraction produced an average value, standard deviation and contrast from image pixel. The contrast value was obtained from the comparison between the standard deviation and the mean value. Data would be classified using the k-means algorithm based on contrast value into 3 clusters that is unripe, ripe, and overripe. The results of the research had shown that in the second experiment with 90 sample data with various levels of ripeness it produces 71% accuracy, with 64 sample data identified correctly. In the third experiment with 64 sample data with relevant contrast values resulting 100% accuracy which means all data was identified correctlyenclassificationoil palmk-meansripenessArticle