The TKDN (Domestic Component Level) assessment of goods and services is a method to determine local manufacturers/industrie’s capability to create quality products internationally standardized. This study assessed the salt factory's TKDN to increase the NaCl content, based on cost-based analysis stipulated at the Minister Industry Regulation No.16/M-IND/PER/2/2011. Meanwhile, the TKDN of salt production was assessed based on process-based analysis stipulated in Minister Industry Regulation No.16/2020. According to the cost-based analysis results, the goods and services at the pilot project stage had the TKDN value of 27.4%. However, due to an increase in the number of main domestic components at the commercial stage, this value increased to 70.9%. Meanwhile, according to the processed-based analysis results, the salt production had the same processes at the pilot project stage and commercial stages. The TKDN value of 85.5% was obtained for the two stages. The value is relatively high because the raw material is produced locally with the local labor and used work tools owned by the local industry. The cost-based analysis was found to be highly dependent on the equipment component’s origin, while the process-based analysis depends on the origin of labor, works tool, and material owner.
Keywords: domestic component level; process-based analysis; cost-based analysis; salt factory; salt product.
In order to tackle the COVID-19 pandemic, the government issued a large-scale social restriction policy (PSBB). The policy in the form of restrictions on social activities will limit economic activity which ultimately has an impact on decreasing energy demand. This PSBB policy is challenge in implementing a national energy management plan, and might causes some of the energy planning targets not to be achieved. To analyze the effect of the COVID-19 pandemic on national energy demand, an energy model was created using LEAP software. LEAP is a model for comprehensive energy planning from energy resources to energy use based on an accounting system. For the purposes of analysis, LEAP requires quite detailed data, in the form of socioeconomic data, energy data, and community activity data due to social restrictions. In this paper, the results of energy modeling simulation are discussed in terms of energy demand based on the scenario of no pandemic or bussiness as usual (BAU) and three pandemic scenarios, namely: optimistic (OPT), moderate (MOD), and pessimistic (PES) scenarios. Energy demand in 2020 is predicted to decrease by 10.7% (OPT scenario), 15.3% (MOD scenario), and 20.0% (PES scenario) compared to the BAU scenario. The model can still be further developed to analyze the impact, both on the overall of demand side and energy supply side and also environmental aspects.
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