Rasyida, Mugia (2020) NAÏVE BAYES CLASSIFICATION UNTUK PENENTUAN STATUS PENDUDUK MISKIN. Jurnal Informatika Kaputama (JIK), 4 (2). pp. 175-180. ISSN 2685-5240

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Poverty is a condition of the community that physically has limited access to adequate basic environmental facilities and infrastructure. The study will classify the poor population in Warudoyong District to reduce the receipt of government assistance that is not on target so as to reduce poverty evenly. This classification uses data mining techniques using the Naïve Bayes Classification method. The parameters used are Age, Dependency, Employment, Education, Income / month, Participation in KPS Program, KIS / JKN, PKH. Some of the advantages of the Naïve Bayes Classifier method are that it is fast, has space efficiency, and only requires a small amount of training data to estimate the parameters needed for classification. The expected outcome of this research is to obtain information / data on the poverty level of the Warudoyong Subdistrict community that can be used by the sub-district to be able to design strategies to improve community welfare. The classification system of the poor population of Warudoyong Subdistrict is based on the results of the confusion matrix test, the use of the Naïve Bayes classification method based on test data taken from the research object obtained an accuracy rate of 70%, a recall value of 66% and a precision of 80%.

Item Type: Article
Uncontrolled Keywords: Poverty, Data Mining, Classification, Naïve Bayes
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Sains dan Teknologi > Teknik Informatika
Depositing User: Perpus ID UMMI
Date Deposited: 21 Apr 2021 04:09
Last Modified: 21 Apr 2021 04:09

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