@thesis{thesis,
		author={JANOTTAMA  LAKSAMANA NUGROHO NAGARA and Yosrita  Efy and Yudho  Satrio},
		title ={EKSTRASI FITUR DOMAIN WAKTU DAN KLASIFIKASI SINYAL EEG MENGGUNAKAN SVM UNTUK IMAJINASI KATA},
		year={2021},
		url={http://156.67.221.169/4913/},
		abstract={This study aims to classify 8 words, namely ?eat?, ?drink?, ?hungry?, ?thirst?,
?happy?, ?sad?, ?sick?, and ?toilet? in the condition of reading silently and imagining the
word. with 0.5 second time domain extraction. In this research case, the author uses a
support vector machine model or method with 3 variations of kernel functions, namely the
Radial basis function, Linear, and Sigmoid kernels. The results obtained by the author in
his research using the support vector machine algorithm with the best kernel, it is found
that the results of 8 heart condition words get 22% accuracy with precision (08%, 30%,
35%, 42%, 22%, 0%, 22 %,30%),Recall(12%,50%,20%,12%,47%,0%,24%,22%),
F1_score (10%, 37%, 25%, 19%, 30%, 0%, 23%, 25%) while for 8 condition words
imagine getting 21% accuracy with precision (25%, 17%, 25%, 26%, 19%, 24%, 07%,
29%), Recall (38 %, 13%, 11%, 30%, 28%, 22%, 25%, 29%), F1_score (30%, 15%, 15%,
28%, 22%, 23%, 11%, 29%) .}
		}