Analisis Data Mining Naive Bayes Klasifikasi Pada Kelayakan Penerima PKH

 (*)Sri Ramadani Mail (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
 Nur Zannah sekar Ayu (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
 N Nurhayati (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
 Fahrija Azzahra (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
 Agus Perdana Windarto (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)

(*) Corresponding Author

DOI: http://dx.doi.org/10.30865/komik.v4i1.2726

Abstract

Abstract Family Hope Program (PKH) is a government program that has been running since 2007 which is a poverty reduction program through the provision of cash assistance to very poor families based on the terms and conditions set. In the implementation of PKH in Limbong Village, Dolok Merawan District, this cannot be maximized because there are still many poor families that have not been channeled by the PKH program so that the funds channeled are not on target. Thus, the classification method is able to find models that distinguish data concepts or classes, with the aim of being able to estimate the class of an object whose label is unknown. Therefore, the Naive Bayes algorithm can predict future opportunities based on past experience. So this research conducts data processing using data mining to classify the eligibility of PKH recipients with the classification method using the Naïve Bayes algorithm, which is expected that the data generated from the data mining process can be an evaluation.

Keywords: Data Mining, Naïve Bayes Algorithm, Classification, PKH

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References

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