KLASIFIKASI PENERIMAAN BANTUAN LANGSUNG SEMENTARA MASYARAKAT (BLSM) DENGAN METODE NAÏVE BAYES (STUDI KASUS : KELURAHAN PEKAUMAN KECAMATAN GRESIK)

DUITA, GRESIKA (2016) KLASIFIKASI PENERIMAAN BANTUAN LANGSUNG SEMENTARA MASYARAKAT (BLSM) DENGAN METODE NAÏVE BAYES (STUDI KASUS : KELURAHAN PEKAUMAN KECAMATAN GRESIK). undergraduate thesis, Universitas Muhammadiyah Gresik.

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Abstract

Gresik is an area that became one of the targets disbursements Temporary Direct Assistance Society Community (BLSM), particularly in Sub Pekauman District of Gresik. Based on observations in the field, in the determination of the people entitled to receive funds Pekauman BLSM in Sub District of Gresik was less objective, where several families are not eligible to receive funds BLSM. The classification system acceptance Temporary Direct Assistance Society (BLSM) is expected to help the Pekauman village particular village secretary to be more objective in determining the public entitled to receive, and not be eligible for Community funding While the Direct Assistance (BLSM) in Pekauman District of Gresik. This research applies data mining classification techniques using naïve Bayes and use the 5 attributes to determine BLSM reception class. The data used are taken from the Head of Family Pekauman village District of Gresik in 2015 as many as 458 data. Based on the testing that was done, the application can generate the information society entitled to receive, and not entitled to receive Temporary Direct Assistance Society (BLSM) in Pekauman village District of Gresik. Accuracy obtained in the test can be seen in Table 4:12 with the highest value of accuracy 99.45%, error value 0.55 %, sensitivity 97.5%, specificity of 100%.

Item Type:	Thesis (undergraduate)
Subjects:	Engineering > Informatics Engineering Engineering
Divisions:	Faculty of Engineering > Informatics Engineering Study Program
Depositing User:	tri risdianto saifullah
Date Deposited:	15 Jul 2019 11:21
Last Modified:	15 Jul 2019 11:21
URI:	http://eprints.umg.ac.id/id/eprint/2004

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