Akurasi Klasifikasi Pengguna terhadap Hotspot WiFi dengan Menggunakan Metode K-Nearest Neighbour

The Current wireless technology is used to find out where the user in room. Utilization of WiFi strength signal from Access Point (AP) can provide information on position a Alternative determination user's room using Receive Signal Strength (RSS). This research was conducted by comparing distance between users 2 or more APs euclidean technique. Euclidean technique as calculator there are two points 3-dimensional plane space measuring length segment connecting points. best for representing and AP. collection RSS data uses Fingerprinting collected 20 detected wifi analyzer application, results scanning, 709 were obtained. value training data. K-Nearest Neighbor (K-NN) Neighborhood Classification predictive new test so that K-NN classify closest existing Based obtained an accuracy rate 95% with K 3. has been done method excellent results, highest minimum error 5%