<![CDATA[This study aims to determine the effect of village fund allocation and village policy on the level of community welfare in Narigunung Village 1. The method used is a quantitative method using the help of Eviews 12. The population in this study was 549 people in Narigunung 1 Village, and the sample in this study amounted to 80 respondents with Non-probability sampling techniques using purposive sampling. Data collection methods by distributing questionnaires and by using validity tests and reliability tests. The data analysis methods used in this study are multiple linear regression analysis, t test, F test, and determination coefficient test. Based on the results of multiple linear regression analysis, the equation Y = 3.422786 + 0.763682X 1 + 0.141002X 2 is obtained, meaning that the constant is 3.422786 which means if X 1 (village fund allocation) and X 2 (village policy) value is 0, then Y (community welfare) value is 3.422786, while X 1 (village fund allocation) with a result of 0.763682 which means that every increase X 1 1% will increase Y by 0.763682% assuming the other variables are constant, and vice versa. and X 2 (village policy) by 0.141002 which means that every increase in X 2 by 1% will increase Y by 0.141002% assuming the other variables are constant, and vice versa. The results of the t (partial) test for X 1 (village fund allocation) obtained a t sig value of 0.0000 < 0.05 which means a positive and significant effect on Y (community welfare) while for X 2 (village policy) a t sig value of 0.0286 < 0.05 was obtained which means a positive and significant effect on Y (community welfare). The results of the F (simultaneous) test are known to have an Fsig value of 0.000000 < 0.05 which means that X 1 (village fund allocation) and X2 (village policy) simultaneously have a significant effect on Y (community welfare). The result of the coefficient of determination obtained R2 (R Square) of 0.731678 or (73.17%), while the remaining 26.83% was influenced or explained by other variables that were not included in this research model]]>
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