Alternative Solutions for Determining Village Funds Using Weight Product Method

Firdiyan Syah, Teknik Informatika, Universitas PGRI Yogyakarta (2020) Alternative Solutions for Determining Village Funds Using Weight Product Method. The 7th International Conference on DV-Xα Method. ISSN IOP Conf. Series: Materials Science and Engineering 835 (2020) 012029 IOP Publishing doi:10.1088/1757-899X/835/1/012029

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Abstract

Based on the Minister of Home Affairs Regulation No. 113 of 2014 concerning Village Financial Management, the management of village funds must be carried out in a transparent, accountable, participatory, orderly, and budgetary discipline. Village fund management starts from January 1 to December 31 of the current year as outlined in the Village Budget (APBDesa). Village budget consists of village income, village expenditure, and Village Financing. The current village fund management mechanism is felt to be too convoluted and filled with obscurity. For example, the measurement for village fund recipients is still based on the results of deliberations. The results of the deliberations that are produced make it possible to have political elements or like-dislike factors. The result will be far from equal distribution and right on target. From this description, we need a tool that is used to help provide a fair decision regarding the recipient of village funds. The tool is a tool that is not influenced by things that cause no equalization and only requires a short time in its processing. So that the recipients of village funds are quickly identified by looking at several criteria. This study provides a solution for determining the recipients of village funds using the Weight Product method. Weight Product Method is one method often used to solve the problem of decision making with many attributes or criteria (MADM). This method is more efficient than some other methods in solving the problem of decision making with many attributes or criteria (Multi Attibute Decision Making). The criteria used in this study include: Poverty rates, area size, geographical difficulties, and infrastructure.

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