Implementasi Data Mining Dengan Naïve Bayes Untuk  Prediksi Penerima Dana BOS Di Sekolah X

Wulan Dari

doi:10.59581/jusiik-widyakarya.v1i3.1230

Authors

Wulan Dari Universitas Potensi Utama, Medan

DOI:

https://doi.org/10.59581/jusiik-widyakarya.v1i3.1230

Keywords:

Data Mining, Naïve Bayes Algorithm, Bos Funding Assistance

Abstract

Schools will receive assistance from recipients of boss funds at school X implementing a program from the government to provide BOS assistance to underprivileged school children in School X. The Bos Assistance Program is a government assistance program in the form of providing cash to underprivileged school children or families capable. Implementation of the program aims to improve the welfare of the less fortunate. Currently, the distribution of Bos Fund Assistance is considered to be still not on target and does not meet the criteria that are used as benchmarks for the people who will receive the assistance. The Naïve Bayes method is used in this case study to classify which children can and cannot afford school fees so that it can more easily select school children or families who are truly eligible to receive the Bos Fund Assistance. This study uses 20 data and 5 criteria including: name, age, gender, status, income, and beneficiary status. After conducting research with a total of 20 data and using the Naïve Bayes method, the results obtained were as many as 45% of underprivileged children and families who were eligible to receive Boss Fund Assistance and as many as 55% of children and families who were not eligible to receive Assistance Boss Fund..

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