Klasifikasi Tingkat Kematangan Buah Kakao Berdasarkan Warna Dengan Metode KNN (K-Nearest Neightbor)

Abstract

Technological developments aim to help facilitate human work in life. The role of technology in human work is very large, one of which is in agriculture and plantations. Classification is a way of grouping objects based on the characteristics possessed by the object of classification. In the process, classification can be done in many ways, either manually or with the help of technology. Cocoa pods certainly have color characteristics to determine the correct level of maturity of cocoa pods. used to classify the maturity level of cocoa pods. This research method uses the scientific method to solve a problem in research, of course the researcher must have a way or a method that is applied in solving the problem so that the research carried out can be resolved properly and in accordance with the expected results. The research method was carried out to look for something systematically using scientific methods and applicable sources, especially in the classification of cocoa pod maturity level based on color using the K-Nearest Neighbor method. The interface design is an illustration of what the cocoa pod maturity classification system will be built using the K-Nearest Neighbor method. An overview of the results is usually made in the form of user interface design or interface design. The K-Nearest Neighbors method can be applied to classify the maturity level of cocoa pods based on ripe and immature colors using matlab software. 2. The results of the image data training process as many as 30 image data are inputted, the training results obtained are 100%. 3. From the feature extraction of red, green, blue, hue, saturation, value and image area of cocoa pods based on color, it can be classified the maturity level of cocoa pods based on color, whether ripe or immature.