Implementasi Histogram Sebagai Ekstraksi Fitur Citra Tanaman Pakcoy Berbasis Metode Nearest Neighbor Untuk Menentukan Kesiapan Panen

Lisa, Pangesti (2021) Implementasi Histogram Sebagai Ekstraksi Fitur Citra Tanaman Pakcoy Berbasis Metode Nearest Neighbor Untuk Menentukan Kesiapan Panen. Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.

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Abstract

Pakcoy plant is one type of mustard vegetables - mustard that has a high potential cultivated in Indonesia because of the relatively fast cultivation time and does not require high maintenance costs. The hydroponic method is one of the pakcoy cultivation methods conducted in Indonesia. To support the acceleration of the implementation of smart farming technology in Indonesia, various methods that support agriculture in Indonesia have been developed. One of the technologies that can be implemented to support the development of Pakcoy cultivation is image processing technology. The image processing technology is used to determine the maturity level of the intensity of greenish colors to determine the readiness of harvest in pakcoy plants. This research aims to create an image processing system that can be implemented in classifying Pakcoy plants that are ready to harvest or not. In this study, the camera was used to take images of pakcoy plants. Furthermore, the pre-processing stage is the stage to change the pixel size of the pakcoy plant image, implement histogram as the extraction of Pakcoy plant image feature, and classify by using Nearest Neighbor using Euclidean distance calculation method. The classifying stage in this system is made into 2 categories namely Pakcoy plants "Ready to Harvest" and "Not Ready to Harvest". The study using imagery as many as 200 pieces of data consisting of 100 mature images and 100 immature images, where 1 image as test image data and 199 images as training image data. The results of this study showed that the implementation of the histogram method by using Nearest Neighbor using Euclidean distance calculation method in determining the harvest readiness of Pakcoy plants has an accuracy rate of 87.43%, precision rate of 87%, and recall rate of 86.13%. This shows that the image processing method can provide good results and can support automation in the cultivation of Pakcoy plants. Keywords: Pakcoy Plant, Smart Farming, Histogram, Euclidean distance

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