Please use this identifier to cite or link to this item: http://repository.unmul.ac.id/handle/123456789/8088
Title: Decision Support System of Direct Cash-Village Fund Recipients Using Multi Attribute Utility Theory
Authors: Ramadiani, Ramadiani
Rahmana, Astrid Rian
Islamiyah, Islamiyah
Balfas, Muhammad Dahlan
Rahman, Tamrin
Yunianta, Arda
Keywords: Direct_Village_Fund_Cas_ Assistance
DSS
MAUT
Issue Date: 29-Dec-2021
Publisher: IEEE
Citation: R. Ramadiani, A. R. Rahmana, I. Islamiyah, M. D. Balfas, T. Rahman and A. Yunianta, "Decision Support System of Direct Cash-Village Fund Recipients Using Multi Attribute Utility Theory," 2021 5th International Conference on Informatics and Computational Sciences (ICICoS), 2021, pp. 232-237, doi: 10.1109/ICICoS53627.2021.9651907.
Abstract: Direct Village Fund Cash Assistance (BLT-Dana Desa) is a form of assistance from the government in the form of cash to poor families in villages sourced from the Village Fund to reduce the impact of the COVID-19 pandemic. To facilitate village officials in determining aid recipients quickly, accurately and on target, the MAUT method was chosen which was deemed suitable for use in the Decision Support System (DSS) which had many criteria so that it could easily calculate each alternative based on the many types of criteria and sub-criteria used and with a predetermined weight. There are 148 data samples of BLT recipients registered in the Social Welfare Integrated Data (DTKS) of Loa Janan Ulu village. The criteria in this study are building floor Size, type of house floor, types of house walls, sanitary facilities, power source, source of drinking water, cooking fuel, consumption of chicken/meat/milk, clothing needs, consumption in a day, do not have savings max. 500.000 rupiah. Based on the results of calculations using the MAUT method, a recommendation for direct cash assistance recipients was obtained with an accuracy value of 92.57%.
URI: http://repository.unmul.ac.id/handle/123456789/8088
https://ieeexplore.ieee.org/document/9651907
ISBN: 978-1-6654-3807-0
ISSN: 2767-7087
Appears in Collections:P - Computer Sciences and Information Technology



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