@thesis{thesis,
		author={Indrianto  Indrianto and Palupiningsih  Pritasari and RAHAYU S  SRY},
		title ={DIAGNOSA PENYAKIT PADA TUMBUHAN SAWI DENGAN METODE HSV DAN SUPPORT VECTOR MACHINE)”.},
		year={2020},
		url={http://156.67.221.169/4290/},
		abstract={The mustard plant is a plant that is widely consumed by people and is also widely cultivated in Indonesia. However, the diseases and pests that often attack the sawi plants result in reduced productivity. The leaf image detection
system works by comparing the previously stored training image data with the image data to be tested. The test image data will be classified using the SVM application method, which serves to classify the class. Each pixel in the image
will be processed to convert the hue, saturation, value (HSV) color features into red, Green, Blue (RGB) first. After obtaining the HSV value, the classification process is carried out using the SVM method. The sample data in the study
used 4 classes of training data classification with 5 data tested in each class data and 25 data tested. In this study, the results obtained from the accuracy of the plant image detection system reached 100%.}
		}