@thesis{thesis,
		author={Cahyaningtya  Rizqia and Rifai  Mochamad Farid and Tubaka  Dyiah Sakina},
		title ={Sistem Pendukung Keputusan Menentukan Prioritas Penerima BANSOS Dampak COVID-19 (Study Kasus : Kantor Kelurahan Desa Hualoy)},
		year={2020},
		url={http://156.67.221.169/4222/},
		abstract={Currently the spread of the Corona Virus has an impact throughout the world as a result of which the economy has stopped. Therefore the Government continues to provide various assistance to the community due to the Corona Virus.
However, several problems often occur, a common problem that often occurs is that it takes one week to select the community that is the priority for beneficiaries, manual data processing has resulted in frequent errors as a result of which the aid has not been fully distributed. The decision support system determines the priority of recipients of social assistance due to COVID-19 using the Naive Bayes method,
the Naive Bayes Method is a method used to predict something based on the probability value of the required criteria, namely Age with P Value = Probability (Yes = 1) and (No = 1), Education P (Yes = 1) and P (No = 1), Occupation P (Yes
= 1) and P (No = 0.76), Income P (Yes = 0.98) and P (No = 1), and Amount Dependent P (Yes = 1) and P (No = 1). The system is built using the PHP programming language and Phpmyadmin as the database. From the test results using 192 data with 182 as training data and 10 as test data, 100% accuracy value,
100% precision value, 100% recall, 167 number of YES Priority data, and 15 NO Priority data.}
		}