@thesis{thesis,
		author={Samsuryadi  and YULIA },
		title ={KLASIFIKASI CUACA BERDASARKAN CITRA AWAN MENGGUNAKAN EKSTRAKSI CIRI HYBRID PRINCIPAL COMPONENT ANALYSIS (PCA) DAN LINEAR DISCRIMINANT ANALYSIS (LDA)},
		year={2018},
		url={https://repository.unsri.ac.id/10064/},
		abstract={Changes in weather and climate conditions have consequences on various sectors of life and greatly affect the activities of human life. Therefore we need a system that can detect weather conditions based on cloud images. The method for detecting weather conditions at one time with image processing is a new innovation that appears in current weather modeling. This is driven by the high need of various parties to conduct research in carefully detecting a condition and without having to observe it directly. The research phase included the image of a cloud converted into a gray image, extracted features using Hybrid PCA and LDA, and classification using the Euclidean Distance method. The results of the study to predict bright, cloudy clouds and rain reached an accuracy rate of 94%.}
		}