Please use this identifier to cite or link to this item: http://repository.uinjkt.ac.id/dspace/handle/123456789/46152
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dc.contributor.authorAlfatta Rezqa Winnersyahid
dc.contributor.authorFeri Fahriantoid
dc.contributor.authorNenny Anggrainiid
dc.date.accessioned2019-07-20T11:27:03Z-
dc.date.available2019-07-20T11:27:03Z-
dc.date.issued2018-08-07-
dc.identifier.isbn978-1-5386-5436-1-
dc.identifier.urihttp://repository.uinjkt.ac.id/dspace/handle/123456789/46152-
dc.description.abstractAs the number of home-based Internet of Things (IoT) applications such as home automation and monitoring of occupants behavior, indoor location information becomes a necessity. Previous research has been able to estimate indoor position using the fingerprinting method. In this paper, proposed a method that is able to estimate the indoor position of the occupants of the house by combining fingerprinting techniques with the home occupants activity pattern using K-Nearest Neighbour algorithm with Euclidean Distance. From the experimental results, this paper get results that the method that the proposed able to estimate with accuracy of up to 87.8% for accuracy below 2 meters with an average error of 0.82 meters.id
dc.description.urihttps://ieeexplore.ieee.org/document/8674367id
dc.language.isoenid
dc.publisherIEEEid
dc.subjectResearch Subject Categories::TECHNOLOGY::Information technology::Systems engineeringid
dc.titleIdentification and position estimation method with K-Nearest Neighbour and home occupants activity patternid
dc.typeWorking Paperid
Appears in Collections:Prosiding Workshop/Lokakarya/Seminar



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