@thesis{thesis,
		author={Elly  Muhammad Jafar and Nursyamsi  Nursyamsi and Palupiningsih  Pritasari},
		title ={Identifikasi Tingkat Kematangan Buah Jambu Kristal Berdasarkan Fitur Warna Menggunakan Metode Transformasi Ruang Warna HSI dan K-Nearest Neighbor},
		year={2020},
		url={http://156.67.221.169/4200/},
		abstract={The crystal guava (Psidium Guajava L) is one of the types of fruit that has commercial value in Indonesia and has a large market share. The problem that occurs is determining the level of fruit maturity that is ready to harvest and grouping
it according to the level of fruit maturity is not accurate. The grouping process is carried out as a whole, so it takes a long time. Each farmer has a different assessment, especially for new farmers. On the basis of the problem at hand, a
system should be a create that can identify the degree of crystal guava fruit maturity. In this study, several steps were carried out to identify the ripeness of the fruit, namely the image preprocessing stage consisting of cropping, resizing and converting the RGB image to the HSI color space. The method used is the HSI color space method as a method of extraction fruit skin color features by looking for the
mean, variance, range of each component of the RGB and HSI. This value is used for calculations to the K-Nearest Neighbor method as a classification method for fruit
maturity. The classification produced in this method of KNN is divided into two classes of mature and semi mature, fruit maturity will be classified according to the testing image into previously established groups or classes, data used in the image of crystal guava with 16 training data and 8 data test data. From testing done on applications comes an accuracy of 87.5%.}
		}