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Jurnal Optimasi Sistem Industri
Published by Universitas Andalas
ISSN : 20884842     EISSN : 24428795     DOI : -
Core Subject : Science, Engineering,
Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mechanical Engineering
Jurnal Optimasi Sistem Industri (JOSI) is a peer-reviewed journal that is published periodically (April and October) by the Department of Industrial Engineering, Faculty of Engineering, Universitas Andalas, Padang.
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Search results for , issue "Vol. 10 No. 2 (2011): Published in 1st October 2011" : 1 Documents clear
Model Proses Adopsi Teknologi di AgroIndustri Lada dengan Fuzzy Inference System Suci Wulandari; Eriyatno Eriyatno; Meika Syahbana Rusli; B. S. Kusmuljono
Jurnal Optimasi Sistem Industri Vol. 10 No. 2 (2011): Published in 1st October 2011
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1341.229 KB) | DOI: 10.25077/josi.v10.n2.p145-153.2011

Abstract

Technology, as one component of agroindustry development system, has a strategic role. It can only be realized if new technology is difussed and adopted. Adoption of technology in the processing of white pepper is still very low. It is therefore necessary to study with the aim to develop a model of agroindustry technology adoption process, and to formulate strategic policy for its acceleration. Model of measuring and predicting user acceptance of new technology is adopted from Unified Theory of Acceptance and Use of Technology (UTAUT) model. Mapping and prediction model technology adoption rates are expressed as a form of usage behavior. The model consists of two parts sub models namely intention to use sub models and support facilities sub model. To deal with vagueness in analysis of technology adoption, fuzzy inference system is used on mapping and level prediction of technology adoption.Keywords: technology, process, model, fuzzy inference system, agroindustry

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