@thesis{thesis,
		author={Firdaus  and NANDA HASYIM  and Reza Firsandaya },
		title ={SISTEM ESTIMASI POSISI DI DALAM GEDUNG BERTINGKAT MENGGUNAKAN METODE FINGERPRINT BERDASARKAN SUPPORT VECTOR MACHINE (SVM)},
		year={2019},
		url={https://repository.unsri.ac.id/24449/},
		abstract={The Position Estimation System in this study uses the location of a multi-story
building, the D building of the Faculty of Computer Science, Indralaya University.
This research continues from previous research which only uses 1 floor. This
research was conducted 2 offline trials, the first experiment used 1 floor with 5
features and the second experiment used 3 floors with 10 features. The results of
the first trial training data yielded a percentage of 89% and the second trial resulted
in a percentage of 98%. The use of the Support Vector Machine (SVM) Kernel
Gaussian Radial Base Function (RBF) algorithm for testing the ownership rating
system reaches 86.87% for the rating labels in this study.}
		}