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All Journal JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Hizkia Juan Suryanto
Universitas Kristen Duta Wacana
Computer Science & IT

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Indoor Positioning System dengan Algoritma K-Means dan KNN Hizkia Juan Suryanto; Antonius Rachmat C.; Yuan Lukito
Jurnal Teknik Informatika dan Sistem Informasi Vol 2 No 3 (2016): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v2i3.641

Abstract

Indoor Positioning System (IPS) can determine someone’s position inside a building. The common method used is implemented by WiFi signal strength analising. This paper discusses about how to do IPS using K-Means and K-Nearest Neighbor (KNN) method, that also analyze the accuracy. K-Means is used to cluster dataset. Each data in certain cluster then classified using KNN method. The dataset consists of 11658 Received Signal Strength (RSS) from 177 Access Point (AP) in UKDW. Accuracy of system analized using 10-fold Cross Validation method which is applied in a range of k=2 to k=11 for clusterisation process, then k=1 to k=5 for classification process. Based on the experiment results, system can determine someone’s position with 88.49% accuracy which k optimum is 10 for clusterisation process, and k=1 for classification process.
Co-Authors Antonius Rachmat Chrismanto Yuan Lukito