ESTIMASI LOKASI OBJEK DALAM GEDUNG BERTINGKAT BERBASIS IEEE 802.11 MENGGUNAKAN METODE NA�VE BAYES
WLAN has become very popular in public and enterprise networking during the last few years. IEEE 802.11 is currently the dominant local wireless networking standard. It is appealling to use an existing WLAN infrastructure for indoor location based WLAN positioning system using RSS from APs that have...
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| Main Authors: | , |
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| 格式: | Theses and Dissertations NonPeerReviewed |
| 出版: |
[Yogyakarta] : Universitas Gadjah Mada
2012
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| 主題: | |
| 在線閱讀: | https://repository.ugm.ac.id/100569/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=57130 |
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| 總結: | WLAN has become very popular in public and enterprise networking during the
last few years. IEEE 802.11 is currently the dominant local wireless networking
standard. It is appealling to use an existing WLAN infrastructure for indoor location
based WLAN positioning system using RSS from APs that have been available.
This research focused on implementation of RSS from APs inside and around the
JTETI UGM building without placing additional APs. RSS fingerprint are collected with
four different measuring orientation, which is North, East, South and West, with gridsize
1m x 1m and 2m x 2m. RSS fingerprint from first, second and third floor are
collected in order to differentiate multifloor. Location estimation of the object is
calculated by Naïve Bayes and k-Nearest Neighbor (k-NN) algorithm as comparator.
As the results, location estimation is influence by fingerprint grid-size, algoritm
and fingerprint measuring orientation. Naïve Bayes method with grid-size 1m x 1m
gives highes accuracy. The acuracy given by this method is 3.41 m. This system has
capability to differentiate between the floors. |
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