The application of soft system methodology to design the conceptual model for intelligent supply chain model of natural fibre agroindustry

Nurhasanah, Nunung and Machfud, Machfud and Mangunwidjaja, Djumali and Romli, Muhammad (2020) The application of soft system methodology to design the conceptual model for intelligent supply chain model of natural fibre agroindustry. IOP Conference Series: Materials Science and Engineering, 847. ISSN 1757-899X

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Official URL: https://iopscience.iop.org/article/10.1088/1757-89...

Abstract

Soft system methodology in designing an intelligent supply chain is defined as a system-based method that is holistically constructed without reduction, according to representation from the real world, coming from stakeholders interacting one to another to gain value added and improve profits through data training and data saving on cloud presented from human to system of real-world database. This study aimed to apply a soft system methodology approach in designing an intelligent supply chain model of natural fibre agroindustry. A conceptual model was successfully developed and produced eight activities which were compared though assessment criteria of efficiency, efficacy, and effectiveness. The eight activities mentioned are productivity improvement, data mining to predict demand and stock, development of a collaborative planning forecasting and replenishment model, development of an intelligent decision support system, digital platform construction, value added improvement, enhancement of efficiency and response to buyers, as well as improvement in supply chain performance. This study has not yet carried out the stages of taking action to improve the problem situation, and will be carried out in further study.

Item Type: Article
Uncontrolled Keywords: Collaboration, intelligent decision support system, performance, value added, data mining
Subjects: 600 Applied sciences & technology > 620 Engineering > 621 Applied Physics
600 Applied sciences & technology > 650 Management & public relations > 658 General Management
Divisions: Universitas Al-Azhar Indonesia (UAI) > Fakultas Sains dan Teknologi (FST) > Teknik Industri
Depositing User: Rifda Jilan
Date Deposited: 08 Apr 2023 03:27
Last Modified: 26 May 2023 08:57
URI: http://eprints.uai.ac.id/id/eprint/2190

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