A FRAMEWORK SOFT COMPUTING IN DSS FOR ALLEVIATION OF POVERTY OPTIMALIZATION IN INDONESIA
Keywords:DSS, Fuzzy Inference, Poverty alleviation fund, Tsukamoto method.
According to BPS (Statitics Indonesia), the number of poor citizens – citizens whose monthly per capita income is lower than the poverty line - in Indonesia in March 2016 was reaching 28,01 million of people or equivalent to 10,86 percent of the total population in Indonesia. The problem must be resolved by a systematic and structured immediately. By innovation in information technology systems so the poverty reduction can be measured with good response. This research attempts to provide a framework soft computing that can optimize decision
support system (DSS) to reduce poverty. Fuzzy inference by Tsukamoto method can be an alternative method to identificate and clustering poverty alleviation fund from government or private parties. This framework is integrated with spatial data poor families, with the location input and mapping as a feature for public audit. The result of this framework has been used by the government in Bantul District, Indonesia, for assisting distribution of poverty alleviation fund to the right people..
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