Abstract

In an effort to reduce the burden on family budgets, the government implemented the Poor Rice Program (Raskin), a social security program for the poor that offers subsidized rice assistance to low-income households. However, in practice, many households are categorized as poor even though they should not be. On the other hand, poor families should be involved, but are not included, and the process is still seen as less focused. Errors in data processing procedures can occur because Raskin recipients are still determined by human data processing. Data processing is time consuming, especially when it comes to ranking and decision making. In this regard, this research explores ways in which Decision Support Systems (DSS) can encourage faster and more precise decision making. Simple Additive Weighting (SAW) and Weighted Product (WP) are the two main methods covered. To increase the effectiveness and accuracy of government aid programs in Indonesia, the main objective of this research is to compare the use of SAW and WP techniques in making decisions regarding the receipt of Rice Miskin aid. The findings of this research support each other by referring to local residents with the pseudonyms W3, W12, W9 , W11, and W17 as recipients of rice assistance from regional governments who are inadequate in decision-making authority positions. Keywords: Decision Support System(DSS),Raskin, Simple Additive Weighting, Weighted Product.

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