SISTEM ESTIMASI POSISI BERBASIS WLAN MENGGUNAKAN KLASIFIKASI FUZZY KNEAREST NEIGHBOR (FK-NN)

MARDIAH, MARDIAH and Malik, Reza Firsandaya (2018) SISTEM ESTIMASI POSISI BERBASIS WLAN MENGGUNAKAN KLASIFIKASI FUZZY KNEAREST NEIGHBOR (FK-NN). Undergraduate thesis, Sriwijaya University.

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Abstract

Increasing the number of public hotspots using Wi-Fi technology is one of opportunity to gain advantage for proposing many new technologies. One of emerging technology is an estimation system to locate the object/person position using Wi-Fi. The object estimation position is the technology to estimate object position accuracy, using signal Received Signal Strength (RSS) from Wi-Fi Access Point. The RSS is an information about the strength of the signal indicates the distance between the access point device. Through the Indoor Positioning System (IPS), RSS value information from multiple access points are processed in order to provide position information. In this study, the IPS using Fuzzy K-Nearest Neighbour (FK-NN) classification method which is a combination of Fuzzy algorithm and K-NN to increase the accuracy of the object estimation position based on the learning data (reference point) where located closest to the object. Through hybridization from the algorithm is expected to calculate the position estimation more effectively and accurately and minimize errors in estimation. The results show that the algorithm FKNN with k = 1 obtain the average location error of 1.2 meters and k = 10 the average location error of 2.8 meters.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Indoor Positioning System, RSS, Fuzzy K-Nearest Neighbour
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA174.A385 Engineering design--Data processing. Manufacturing processes--Data processing. Computer integrated manufacturing systems. Manufacturing processes--Automation. CAD/CAM systems.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Mrs Sri Astuti
Date Deposited:	30 Sep 2019 01:56
Last Modified:	30 Sep 2019 01:56
URI:	http://repository.unsri.ac.id/id/eprint/9528

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