| Oil fuel (Bahan Bakar Minyak) or commonly shortened as BBM was one of the needs that’s crusial in daily life. Because of the need for this fuel is very high, so the government gave help in the form of subsidy to reduce the price of fuel. The government gave this subsidy because fuel’s global price keeps soaring. This subsidy that was given by the government was given to oil refining sector to reduce fuels’ price that was produced. But, as a result of this fuel subsidy is the APBN keeps soaring high. The government has made an attempt to doing the reduction of fuel subsidy. But when the fuel subsidy was reduced then it will affect economic sectors which later on will affect to the increasing of commodities’ price. The increasing of this commodity’s price will affect the economy in Indonesia and will affect Indonesia’s household. The impact of this fuel subsidy policy on household will be researched in this research. This research uses mathematic model to represents actual model to the inside of that equilibrium model. The model that was used in this research is CGE model (Computable General Equilibrium). This model was a mathematic model that can be used to analyse the impact of government’s policy that is done earlier against the existing production, institution and production commodities sectors. This research uses SNSE database (Sistem Sosial Neraca Ekonomi) year 2000 and SNSE 2005. That CGE model then simulated with using the GAMS software (General Algebraic Modeling System). The simulation that was done consists of four scenario. Simulation I is adding fuel subsidy by 30% on year 2000, simulation II is reducing fuel subsidy by 30%, simulation III is increasing fuel subsidy by 30% and simulation IV is reducing fuel subsidy by 30%. The result of the simulation on scenarios that was made is that the fuel subsidy that was done by the government, affects the existing commodity’s price. That price of commodity will impact directly to household in Indonesia. From the result of scenario I, the highest score that occurred on food, beverage and tobacco industry commodity was obtained; simulation scenario II, the highest score that occurred on food, beverage and tobacco industry commodity was obtained; simulation scenario III, the highest score that occurred on food, beverage and tobacco industry commodity was obtained and the result of simulation scenario IV, the highest score that occurred on food, beverage and tobacco industry commodity was obtained. |