Risk Linkage Model for Cooking Oil Supply Chain Model Keterkaitan Risiko Pada Rantai Pasok Minyak Goreng

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Paramaditya Arismawati
Iwan Vanany

Abstract

Cooking oil is one of nine elements of Indonesian staple cuisine, also known as basic food. In the middle of 2022, the public will experience cooking oil scarcity, with prices that are significantly higher than before. The price increase of CPO (Crude Palm Oil) raw materials, disruption of distribution channels, low supplies of domestic palm oil raw materials, and some domestic cooking oil producers exporting without permission from the government and violating the law are some of the causes of the rise in cooking oil prices. As a result, the supply that should be available to Indonesians has been curtailed, and there is a lack of cooking oil. One of the palm oil generating sectors involves supply chain activities that include palm oil suppliers, producers converting it into crude oil, and then sending the crude oil to domestic customers who utilize the crude oil as raw material to make the products they want, namely oil. fry. Unwanted risk occurrences will occur as a result of the supply chain activities that are formed. The goal of this study is to identify risk events, analyze the linkage between risks in the cooking oil supply chain using the DEMATEL-ISM-MICMAC fuzzy technique, and develop risk reduction strategies. DEMATEL fuzzy integration approach for developing structural models including complicated cause-and-effect interactions. Then, using graphs, ISM maps and visualizes risk correlations. The MICMAC approach is used to categorize existing elements based on their dependence power and driver power. The findings of this study found eleven risk events, with shipping uncertainty (R8) being the most influential risk event. To combat shipping unpredictability, the recommended mitigation action strategy is to supply alternative shipping partners.

Article Details

How to Cite
Arismawati, P., & Vanany, I. (2024). Risk Linkage Model for Cooking Oil Supply Chain. PROZIMA (Productivity, Optimization and Manufacturing System Engineering), 7(2), 143-153. https://doi.org/10.21070/prozima.v7i2.1585
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Articles

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