Wulandari, Febri (2019) SISTEM PENGKLASIFIKASIAN PEMILIHAN PENERIMA BERAS MISKIN (RASKIN) MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER (NBC) (Studi Kasus: Kelurahan Tambakmerang, Girimarto, Wonogiri). Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
Distribution of poor or Raskin rice is a routine activity every month that is always carried out by the government to help poor people with food problems. The initial implementation of Raskin aims to strengthen household food security, especially for poor households. However, determining the criteria for beneficiaries of poor rice is often a complex issue. In determining the criteria the recipient is only based on an assessment of subjectivity, so that fraud in the distribution of poor rice increases and results in uneven or misdirected rice. Therefore, research was conducted on determining the recipient of poor rice. This research will use the Naïve Bayes Classifier (NBC) method. The Naïve Bayes Classifier (NBC) method is an approach that refers to the Bayes theorem that predicts future opportunities based on past experience. This method is one of the simple classification categories but has high accuracy besides this method only requires a small amount of training data for estimating the parameters needed in the classification process. Training data for recipients of poor rice will be calculated later on the number of labels. From this data, the same number of criteria per label will be calculated, then multiplication of all label variables. Finally, comparing the results of the data per label to determine the eligibility of poor rice recipients (raskin). Based on the results of the study, it is expected to help determine the classification of the selection of poor rice recipients without any fraud when determining. Keywords: Poor Rice (Raskin), Naïve Bayes Classifier (NBC), Prospective Recipients.
Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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Subjects: | T Technology > T Technology (General) |
Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
Depositing User: | Kaprodi S1 Informatika UTY |
Date Deposited: | 31 Oct 2019 07:23 |
Last Modified: | 31 Oct 2019 07:23 |
URI: | http://eprints.uty.ac.id/id/eprint/3894 |
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