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All Journal ILKOM Jurnal Ilmiah
Sukarna, Royan Habibi
Program Studi Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia
Computer Science & IT

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INDOOR POSITIONING SYSTEM BERDASARKAN FINGERPRINTING RECEIVED SIGNAL STRENGTH (RSS) WIFI DENGAN ALGORITMA K-NEAREST NEIGHBOR (K-NN) Yudha, Dendi Prana; Hasbi, Billy Ibrahim; Sukarna, Royan Habibi
ILKOM Jurnal Ilmiah Vol 10, No 3 (2018)
Publisher : Program Studi Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (748.413 KB) | DOI: 10.33096/ilkom.v10i3.364.274-283

Abstract

Wireless networks other than communication media can be used to find out the existence of an object. Positioning technology that is commonly used is Global Positioning System (GPS). GPS can receive location information accurately in outdoor, this situation is contradictory in indoor environment, GPS signal is interrupted by signal attenuation caused by building materials and types of physical barriers. This study aims as an alternative solution for indoor positioning using RSS (Received Signal Strength) WiFi. Fingerprinting technique is used to collect RSS data on 5 access points in 3 test locations, RSS data collected is 243 data. This study uses Euclidean Distance and K-Nearest Neighbor (K-NN) method. The accuracy of the system is tested using the 10-Fold Cross Validation method based on the results of the test shows that the system is able to determine the location with an accuracy rate of 96.71%.
Co-Authors Hasbi, Billy Ibrahim Yudha, Dendi Prana