KLASIFIKASI PENERIMA BANTUAN RASTRA MENGGUNAKAN METODE NAIVE BAYES

  • Kharomatun Nuruhul Mustofa Alumni Program Studi Teknik Informatika
  • Eka Suswaini Dosen Fakultas Teknik UMRAH
  • Nurfalinda Nurfalinda Dosen Fakultas Teknik UMRAH
Keywords: Classification, Bansos, RASTRA, Naïve Bayes

Abstract

The level of poverty that occurs in the Kab. Bintan especially in the Kuala Sempang Village area is still high, this is seen from the poverty line value which increased by 3.27 percent. The government, through the Prosperous Rice Social Assistance Distribution Program (BANSOS RASTRA) and Non-Cash Assistance in 2018 based on the Decree of the Minister of Social Affairs of the Republic of Indonesia Number 4 / HUK / 2018 shows that Bintan Regency received RASTRA assistance totaling 4,595 households. RASTRA assistance in Kuala Sempang Village uses the poverty criteria used by the Central Statistics Agency (BPS), the parameters used by BPS are floor area, floor type, wall area, lighting source, etc. The test used the Naïve Bayes Method with inputting criteria such as the number of household members, floor area, floor type, wall type, drinking water source, defecation facilities, lighting sources, energy for cooking and PKH status. The test results obtained show that the accuracy value using the amount of testing data of 30%, 60% and 100% has different results, where the highest accuracy value is obtained using 30% and 60% of the data which has 100% results. Whereas for testing the accuracy value using testing data 100% amounted to 96.67%

Published
2021-10-12
Section
Teknik Informatika