The study of poverty reduction is very relevant in the 21st century. The rapid development of technology has proven to improve various quality of life but has not been able to solve the problem of poverty in a total scale. On the other hand, the development of public administration science, especially regarding collaborative governance, provides hope for poverty reduction through the active role of various parties. Many experts explain that poverty is a complex problem. Poverty reduction efforts must be carried out in a holistic and participatory manner. Furthermore, there needs to be an active contribution from various parties, namely the government, the private sector and the community. This requires researchers to conduct further studies on how Collaborative Governance can be an alternative solution to solving the problem of poverty. This study aims to delineate the development of Collaborative Governance studies through the Systematic Mapping Study and associate it to the poverty alleviation to obtain the current research position. The study shows that research on Collaborative Governance for Poverty Reduction is included in Social Issues in Community concentration and it has the lowest percentage. The most widely used method in the research concentrated on Collaborative Governance is qualitative, and the publication trend shows a very significant development, especially in 2014-2018. Therefore, research on collaborative governance for poverty alleviation is still very limited and the opportunity to produce variety of renewals is very large.
The focus of this study is an experiment and simulation of an Organic Rankine Cycle (ORC) system to produce electricity. The experimental equipment consisted of four main components: fluid pumps (for refrigerant and water); a condenser as a heat exchanger to condense the working fluid; an evaporator (boiler) as a heat exchanger to evaporate the refrigerant; and an expander (turbine) as a driver to produce electricity. The expander was a modification of a scroll air conditioning (AC) compressor, with a capacity of 13 kilowatts and connected to the generator to produce electricity in line with the design estimate. Furthermore, based on the application of the ORC experiment in the form of a small-scale power plant, a predetermined temperature setting was set for the heat source, ranging between 80 and 100 o C. The working fluid used in the study was R-134a. Optimum power estimation was obtained by processing the experimental result data using a software cycle tempo simulation that measured several electrical power outputs between 1.76 and 2.74 kilowatts.
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