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Submitted
May 20, 2024
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June 8, 2024
Published
March 1, 2024
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Abstract

Recognition or identification is important to make it easier for us to recognize a type of plant or plant community. Each type has characteristics that have adapted to its habitat. Plants that exist in dry land areas including those around the University of Timor campus, it is necessary to identify or carry out scanning to identify names, characteristics and benefits and status in nature. Scanning is often done manually so that it is sometimes less effective and efficient familiar to the lay public. The aim of this research is to integrate scanning methods with optimizing ICT media such as using the “Sincatanesa” (Plant Scanning System) application with QR Code. The method used is a combination between observation methods and identifying specific tree growth forms and input into the “Sincatanesa” application which has been designed by researcher. Taxonomic data ranging from kingdom to species, habitus, benefits and IUCN status of each existing tree. Then make it QR Code attached to each tree. There were 18 types of trees identified and a QR Code was created for identification in the “Sincatanesa” application. The data stored is internet based so there will be a lot of data that can be stored, can be edited easily It's easy and just scan the barcode to identify the tree. Hopefully this application is known and used by all academic community at the University of Timor and the wider community. Furthermore, the “Sincatanesa” application can be developed based on smartphone so that it becomes more flexible and easier to use.

Keywords

Information Systems, QR-Code, Plants, Land Areas, Scanning System.

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Copyright (c) 2024 TEPIAN

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How to Cite
Nona, R., Ramadhani, F., & Andrea, R. (2024). Development “Sincatensa”, a Plant Sensing System Application in Land Dry Areas Using Qr-Code. TEPIAN, 5(1), 30–34. https://doi.org/10.51967/tepian.v5i1.3023
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