JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Vol 2 No 3 (2016): JuTISI

Indoor Positioning System dengan Algoritma K-Means dan KNN

Hizkia Juan Suryanto (Universitas Kristen Duta Wacana)
Antonius Rachmat C. (Universitas Kristen Duta Wacana)
Yuan Lukito (Universitas Kristen Duta Wacana)



Article Info

Publish Date
10 Dec 2016

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.

Copyrights © 2016






Journal Info

Abbrev

jutisi

Publisher

Subject

Computer Science & IT

Description

Paper topics that can be included in JuTISI are as follows, but are not limited to: • Artificial Intelligence • Business Intelligence • Cloud & Grid Computing • Computer Networking & Security • Data Analytics • Datawarehouse & Datamining • Decision Support System • E-Systems (E-Gov, ...