Pengenalan Tingkat Kematangan Buah Pepaya Paya Rabo (Carica Papaya L) Menggunakan Pengolahan Citra Berdasarkan Warna RGB dengan K-Means Clustering

Abstract

The process of identifyingfruit traditionolly couses many problems because of human weaknesses so that the intended result is not ffictive- The advancement computerization technologt has been irrvolved in agriculture either in pre-harvest periodor post-harvest period . The problem is how to htow whether a certain fruit meets its real condition. The condition of papaya is determined by the ripeness which con be seen from its color. The process of classification conducted by farmers is usually identified by green ripe, not completely ripe, and completely ripe (can be plucked). The image processing method is able to analyze the condition of image by using colour Red, Green, Blue (RGB) yalue as the reference. Classificotion is determined by using K-mean Clustering, utilizing enclidisn distonce voriance as the reference. The outcome of cluster green popoyal 60% of them were succesfully identified os green popoyas, cluster not completely ripe popayas, 90% of them were identified as not completely ripe papayas, and cluster completely ripe papayas, l00ok of them were identified as completely ripe. Therefore, it can be concluded that Kmean Clustering was almost the same as the classification process done by the farmers who had experiencedfor yeors.