Penerapan Algoritma K-Nearest Neighbor Untuk Klasifikasi Warga Penerima Bantuan Sosial
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Pajar Pahrudin
*
STMIK Widya Cipta Dharma, Samarinda,
Indonesia
- Kusno Harianto STMIK Widya Cipta Dharma, Samarinda, Indonesia (*) Corresponding Author
Abstract
Social Assistance (BanSos) is a government program intended for lower-middle families. Social assistance is assistance given to the community, especially the lower middle class, which is not continuous and selective. Many types of social assistance are provided by the government with the aim of prospering and helping the community's economy. However, the problem that occurs is that there are still many people who receive social assistance that are not people who deserve to receive social assistance, while the lower middle class who should receive social assistance are neglected and do not receive the social assistance. It should be for the distributor or the kelurahan to form groups for residents who are entitled to receive social assistance. The process of grouping the recipients of social assistance can be done by processing the data of residents who have the right to receive the social assistance. The data processing can be done by using data mining. One of the algorithms that can be used to solve problems in data mining is the K-Nearest Neighbor algorithm. After carrying out the overall process with a value of K = 5, it was found that the new data from residents was declared eligible to receive social assistance
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References
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