FEASIBILITY TEST OF POOR RICE RECIPIENTS IN BENCOY SUKABUMI VILLAGE USING NAIVE BAYES

Taufik Hidayatulloh; Ardi Winardi; Lestari Yusuf; Satia Suhada; Saeful Bahri

doi:10.33480/pilar.v17i1.2227

Taufik Hidayatulloh Universita Bina Sarana Informatika
Ardi Winardi Universita Bina Sarana Informatika
Lestari Yusuf Universitas Nusamandiri
Satia Suhada Universitas Nusamandiri
Saeful Bahri Universitas Nusamandiri

DOI: https://doi.org/10.33480/pilar.v17i1.2227

Keywords: Naïve Bayes, Data Mining, Poor Rice

Abstract

A regional head must have a work plan every regional head must have a work plan which is sure to be of benefit to the community. Assisting is a definite work plan in every region. A lot of assistance is usually given from the government to the community and must be managed by the village government so that the aid gets to the right hands. And to improve food security, the people in each region have activities to distribute Poor Rice as a subsidy from the government. In the distribution method, sometimes there are constraints in data collection so that poor rice or what we usually call Raskin is not suitable for distribution. Because of this, a way is needed so that the distribution is appropriate or not in the community in accepting the Raskin so that government assistance can be delivered properly and on target. By using secondary data obtained from Bencoy Village, 205 data were obtained containing the attributes of the eligibility category of Raskin recipients, and 6 categories of attributes were found with the classification method of the Naïve Bayes algorithm. The accuracy value obtained is 96.59%, proving that the prediction using the Naive Bayes algorithm has a good performance. The next results obtained are in the form of AUC value which after being calculated produces a value of 0.999 and this results in an application which is an implementation with a flow that is adjusted to the calculation algorithm in the form of a web-based application.

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