ASOSIASI ITEM BELANJA DESA MENGGUNAKAN ALGORITMA APRIORI

The problems that occur are a lot of data contained in village financial institutions, which raises difficulties in terms of village budgeting and expenditure, so it is necessary to implement an a priori algorithm for data on village income and expenditure budgets. The method that will be used in this study is Apriori by analyzing the village income and expenditure budget data. The formation of association rules is obtained by determining the minimum support value of 2% and minimum confidence of 50%. The association rule with the smallest support score and the highest value of confidence, which is 100%, becomes the rule chosen for the reference of bundling strategies in village expenditure items. Apriori Algorithms can be applied to support the Village Expenditure Budget Item. Planning and spending of the Village Budget Item is greatly assisted by the application of this Priori algorithm so that the effectiveness is expected to be increased. The application of the Apriori algorithm which is done through software designed has been shown to show the appropriate results. This is proven by calculating the value of support and confidence which shows the same results.