ALGORITMA NAIVE BAYES UNTUK MEMPREDIKSI KELAYAKAN PENERIMA BANTUAN PANGAN NON TUNAI (BPNT) DESA JAGANG LAMPUNG UTARA

Authors

  • Rustam Institut Teknologi Bisnis Dan Bahasa Dian Cipta Cendikia
  • Yanike Anestasya Anggraeny Institut Teknologi Bisnis Dan Bahasa Dian Cipta Cendikia
  • Septa Institut Teknologi Bisnis Dan Bahasa Dian Cipta Cendikia
  • Dwi Marisa Efendi Institut Teknologi Bisnis Dan Bahasa Dian Cipta Cendikia

DOI:

https://doi.org/10.34151/prosidingsnast.v1i1.5136

Keywords:

Feasibility, Data Mining, Naïve Bayes, RapidMiner

Abstract

Jagang Village is a government agency in Blambangan Pagar District, North Lampung Regency. Jagang Village runs a government program, namely the Non-Cash Food Assistance (BPNT) program in running the program, some residents who are considered capable actually get assistance. In this study, the method used in predicting the eligibility of recipients and non-recipients of Non-Cash Food Assistance (BPNT) is the Naïve Bayes method with manual calculations using Excel formulas that are composed in such a way as to facilitate data input and testing using RapidMiner 7.1 and produces the same accuracy as manual calculations. The results of the implementation of Data Mining using the Naïve Bayes Method to predict the Eligibility of recipients and non-recipients of Non-Cash Food Assistance (BPNT) obtained a prediction accuracy value of 91% and was tested with RapidMiner software with an Accuracy result of 90.91%.

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Published

23-11-2024

Issue

Prosiding SNAST 2024

Section

Articles

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Copyright (c) 2024 Rustam, Yanike Anestasya Anggraeny, Septa, Dwi Marisa Efendi

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