Introduction: Waste processing in Final Disposal Sites (FDS) in Indonesia is still dominated by open dumping. This condition causes health and environmental problems and inhibits the achievement of Sustainable Development Goals (SDGs) 2030. Waste is biomass that can be converted into electrical energy through the Waste-to-Energy Plant (WtE Plant) installation. This article aimed to illustrate the potential of WtE Plant in the FDS in Indonesia in supporting the achievement of SDGs 2030. Discussion: Most waste in the FDS are dominated by organic waste with the highwater content of 60-70% but have a calorific value almost equivalent to sub-bituminous coal. Most studies show the WtE Plant uses a thermal method (incinerator) than other technologies because it has a superior value in the technical aspects (easy operation and high generated energy around 9.86%), economy aspects (medium investment value, but high profit with moderate payback period around 6.5 years) environmental aspects (reduction of waste up to 70-80% and emissions), and lower public health impacts than those produced by open dumping and coal systems. For environmentally safe optimal results, it is necessary to reduce wastewater content, increase pollution control units, and implement an integrated monitoring system. Conclusion: The implementation of WtE Plant can accelerate to achieve the SDGs 2030, especially the 7th, 8th, 12th, and 13th goals concerning clean and affordable energy, decent jobs and economic growth, responsible consumption and production, and addressing climate change, respectively.
COVID-19 (Coronavirus Disease 2019) continues to be a global issue. The disease began to spread due to direct contact with the seafood market in Wuhan, Hubei Province, China. COVID-19 cases globally and especially in Indonesia, are still increasing as well. Therefore, it is important to forecast future cases as a form of vigilance and materials to formulate strategies in controlling the spread and procurement of health systems. This study aims to predict daily cases of COVID-19 in Indonesia. This research includes non-reactive studies by collecting daily case data on COVID-19 from October 1st to December 31st, 2020 from the COVID-19 Task Force website in Indonesia. The results showed that the model that is fit to describe COVID-19 cases in Indonesia is ARIMA [5,1,0] with a model significance of 0.000 and constant of 0.049 (p value <0.05), Ljung-Box Q of 0.880 (p value >0.05) and residual normality of 0.330 (p value >0.05). The three months forecasting (from January to March 2021) showed a number that tended to increase. The increase in cases occurred due to environment, behavior, health services, and genetics. Therefore, it is necessary to increase cooperation between the government and the community so that efforts to suppress the growth of COVID-19 cases are optimal.
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