Model penyeimbangan nilai tambah berdasarkan tingkat risiko pada rantai pasok minyak sawit

Abstract

In palm oil supply chain the smallholder farmers sell their fresh fruit bunch (FFB) to Palm Oil Mills through traders. Palm Oil Mills convert the FFB into crude palm oil (CPO). CPO is sold to the refinery, who converts CPO into frying oil and sends the product to the distributors. The distributors subsequently sell them to the consumers. The risk levels between the actors may not be proportionately rewarded by the same levels of added value. The objectives of this study are to identify and evaluate the risks faced by the actors, to find or improve a formula to calculate the added value for all actors successively, to design a model to simulate the interactive behaviors of the palm oil supply chain actors, and to facilitate optimum distribution of the added value for each actor, while considering the successive investment and risk levels. Information obtained from the interviews with selected experts and industry players were processed using Fuzzy Analytic Hierarchy Process (FAHP). From the 12 risks identified the result converged into supply continuity and product quality risks. In this study the original Hayami method was modified to calculate the added value for all actors successively. The price of the output product from one actor became the input cost for the next actor, this went on until the end of the chain. The modified Hayami method can also measure the added value levels between all supply chain actors. Netlogo agent-based modeling tool was used for this purpose as it provided the best means to identify and study the supply chain actors (or agents) behaviors. To facilitate fair distribution of rewards for the supply chain actors a concept of added value utility based on investment and risk level was introduced. To optimize the added value distribution between the agents the concept of stakeholder dialogue was used. The selling prices were negotiated between the actors until each reached a satisfactory value, which was ruled by the levels of optimum added value utility. This research is important because the developed model may facilitate a better formula to calculate the fair distribution of added value among the actors, therefore ensure its sustainability and improve the total supply chain added value.