Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes

The main problem in the current poverty reduction effort is related to the fact that economic growth is not evenly distributed. The research will classify based on the data of poor people obtained from Tibawa District by using data mining technique. Attributes to be used in classifying the populatio...

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Main Author: Haditsah Annur
Format: Article
Language:English
Published: Fakultas Ilmu Komputer UMI 2018-08-01
Series:Ilkom Jurnal Ilmiah
Subjects:
Online Access:http://jurnal.fikom.umi.ac.id/index.php/ILKOM/article/view/303
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author Haditsah Annur
author_facet Haditsah Annur
author_sort Haditsah Annur
collection DOAJ
description The main problem in the current poverty reduction effort is related to the fact that economic growth is not evenly distributed. The research will classify based on the data of poor people obtained from Tibawa District by using data mining technique. Attributes to be used in classifying the population are Age, Education, Work, Income, Dependent, Status (Married / Unmarried). The method to be used is the Naïve Bayes Classifier method, which is one of the classification techniques in data mining. Based on the research, it is concluded that, the classification system of the poor in the administrative area of Tibawa sub-district, Gorontalo regency can be engineered and Based on the result of confusion matrix testing with split validation technique, the use of naïve Bayes classification method to the dataset which has been taken on the research object obtained the level of accuracy 73% or included in the Good category. While the Precision value of 92% and Recall of 86%.
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spelling doaj.art-def85147a0e448749e6431026bb237232022-12-21T21:32:21ZengFakultas Ilmu Komputer UMIIlkom Jurnal Ilmiah2087-17162548-77792018-08-0110216016510.33096/ilkom.v10i2.303.160-165131Klasifikasi Masyarakat Miskin Menggunakan Metode Naive BayesHaditsah Annur0Universitas Ichsan GorontaloThe main problem in the current poverty reduction effort is related to the fact that economic growth is not evenly distributed. The research will classify based on the data of poor people obtained from Tibawa District by using data mining technique. Attributes to be used in classifying the population are Age, Education, Work, Income, Dependent, Status (Married / Unmarried). The method to be used is the Naïve Bayes Classifier method, which is one of the classification techniques in data mining. Based on the research, it is concluded that, the classification system of the poor in the administrative area of Tibawa sub-district, Gorontalo regency can be engineered and Based on the result of confusion matrix testing with split validation technique, the use of naïve Bayes classification method to the dataset which has been taken on the research object obtained the level of accuracy 73% or included in the Good category. While the Precision value of 92% and Recall of 86%.http://jurnal.fikom.umi.ac.id/index.php/ILKOM/article/view/303poverty leveldata miningclassificationnaïve bayes
spellingShingle Haditsah Annur
Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes
Ilkom Jurnal Ilmiah
poverty level
data mining
classification
naïve bayes
title Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes
title_full Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes
title_fullStr Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes
title_full_unstemmed Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes
title_short Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes
title_sort klasifikasi masyarakat miskin menggunakan metode naive bayes
topic poverty level
data mining
classification
naïve bayes
url http://jurnal.fikom.umi.ac.id/index.php/ILKOM/article/view/303
work_keys_str_mv AT haditsahannur klasifikasimasyarakatmiskinmenggunakanmetodenaivebayes