Klasifikasi Data Bantuan Sosial pada Desa Sindangpano dengan Menggunakan Algoritma K-Nearest Neighbor - Wulan Suci; Nining R; Fadhil M. Basysyar (Ma'soem University, 2022)
Since the emergence of the Covid-19 Pandemic, many people have joined affacted, one of which is people who have lost their livelihoods. In this study the data used is data on social assistance in the village of Sindangpano in 2021. The data will be processed using the data mining method the k-Nearest Neighbor (KNN) algorithm. One of the them is the emergence ofsocial jealousy between communities. In this study using data mining methods that are assisted by using the K-Nearest Neighbor (KNN) Algorithm and sopported by existing data using Knowlage Discovery Data (KDD) data mining techniques with data selection, transformation, data mining and evaluation in the distribution of social assistance in Sindangpano Village, there are often many problems because people think that the social assistance is distributed is not righ on target so that many people feel that they are not being noticed by the government. Problems that are often found are social jealousy. Among the people this is caused by a lack of information, communication and education by the government to the comunity. This teseach was made with the hope of producing a solution to a problem, so that it can solve many problems that occur in the distribution of Social Assistance in Sindangpano of Village. The results obtained from this classification trial an accuracy rate of 99.57% with a Village Fund precision of 99.50%, BPNT is 99.62%. and the recal result from the Village Fund are 99.50%, BPNT 99.62%. The result of this classification can also be seen what percentage of the community received the assistance, so that the level of balance in the number of recipients can be seen