@thesis{thesis,
		author={RABANI  MOHAMAD BAHARUDDIN},
		title ={SISTEM KLASIFIKASI KELUARGA SISWA MAMPU DAN TIDAK MAMPU UNTUK MENDAPATKAN BEASISWA DI MA MUHAMMADIYAH 1 SUMBERREJO
KAB. BOJONEGORO DENGAN MENGGUNAKAN METODE NAÏVE BAYES},
		year={2014},
		url={http://eprints.umg.ac.id/1523/},
		abstract={Scholarship is important for students' families can not afford, which is to help prekonomian families and students are not able to alleviate the funds to go to school, one of APBD that funds scholarships every year in scholarship money distributed to poor families that will help the economy of the student's family can not afford , but the scholarship funds are misappropriation of funds from certain parties, so that the flow of funds is not on target. Therefore, we need a classification system of the student's family is able and not able to get a scholarship, making it easier to distribute Principal's performance APBD funds with more targeted. This study uses data mining classification technique using Naïve Bayes method for classifying student class families are able or not able to a family. Attributes used in this study comprised seven variables, namely the number of siblings, number of half-brothers, number of sisters who work, the amount of your income, father's occupation, mother's occupation and the average monthly income of the parents. Testing the system testing performed three times, using different training data. The data used in the testing of this system is the result of a survey of school when new students at MA Muhammadiyah 1 Sumberrejo kab.Bojonegoro academic year 2013/2014, a total of 105 data. Based on the results of the third test, the highest accuracy rate in the third test which has an accuracy of 86.67%.}
		}