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dc.contributor.authorSeptiawan, R
dc.contributor.authorShanmuganathan, S
dc.contributor.authorKomaruddin, A
dc.contributor.authorSulistya, B
dc.contributor.authorNur, A
dc.date.accessioned2012-12-10T21:23:49Z
dc.date.available2012-12-10T21:23:49Z
dc.date.copyright2012-11-21
dc.date.issued2012-12-11
dc.identifier.citation2nd International Conference on Intelligent Systems and Informatics 2012 held at Auditorium Mgr Geise Parahyangan Catholic University (UNPAR) Jl. Ciumbuleuit 94, Bandung, Indonesia, 2012-11-19to 2012-11-21, published in: Prediction Model for Chilli Productivity Based on Climate and Productivity Data, pp.1 - 6 (6)
dc.identifier.urihttp://hdl.handle.net/10292/4838
dc.description.abstractThe global trade increases the competition in agricultural product export all around the world.The Indonesian Agricultural Industry needs to improve their competitiveness by fulfilling the requirements and restrictions imposed by some countries with regards to traceability information features of the products, such as location of farming field cultivation method, chemical contaminants and supply chain information. Some European countries require the implementation of E-GAP (European Good Agricultural Practices) in order to secure food safety. Food safety provides the control and monitoring during, pre-, and post-harvest stages of agricultural products. This paper describes a prediction model based on the climate and productivity data on Indonesian agricultural products. The prediction model with an iteration of the climate and their possible increase or decrease in productivity. The model relies on historical data and an analytical algorithm. The decision support and early warning system provides the farmer some advice to reduce the crop failure risks due to climate change
dc.publisherIEEE
dc.relation.isreplacedby10292/5246
dc.relation.isreplacedbyhttp://hdl.handle.net/10292/5246
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in (see Citation). The original publication is available at (see Publisher's Version)
dc.subjectField monitor
dc.subjectPrediction model/iterative model
dc.subjectTraceability
dc.titlePrediction model for chilli productivity based on climate and productivity data
dc.typeConference Contribution
dc.rights.accessrightsOpenAccess
dc.identifier.doi10.1109/EMS.2012.67
aut.conference.typePaper Published in Proceedings
aut.relation.endpage6
aut.relation.pages6
aut.relation.startpage1
pubs.elements-id132019


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