Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/77227
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dc.contributor.advisorErfiani-
dc.contributor.advisorSartono, Bagus-
dc.contributor.authorSrikandi, Dina-
dc.date.accessioned2016-01-08T22:06:58Z-
dc.date.available2016-01-08T22:06:58Z-
dc.date.issued2015-
dc.identifier.urihttp://repository.ipb.ac.id/handle/123456789/77227-
dc.description.abstractEducation is one of the children’s rights as young generation successor to the nation that must be met by the government. According to Law No. 23 of 2002 Article 4 concerning the protection of children, child is defined as someone who hasn’t 18 years old. One of the rights of children which must be met by the government is the right to education. The government's success in meeting its obligations can be seen from how big the school dropout rate. One factor that can be measured by the low level of education is high dropout rates. In 2012, dropout rate for children 7-17 years old in all province at Sulawesi were still higher than national rate. To overcome these problems, efforts are required to identify and search factors that cause of dropouts. The socio-economic and demographic factors or environmental factors, especially social network effect in children’s live, so that the measures taken by the government can be precisely targeted. To determine the characteristics of dropout students require to clasify the children 7-17 year old using classification and regression tree (CART) method and then apply the Bagging techniques. This study aims to determine how the characteristics of dropout students 7-17 years old that more detailed in Sulawesi. Classification is built not only consider the socio-economic and demographic factors but also adds social network factors. Furthermore, it will be seen how the effect of these factors into the classification by looking the classification accuracy. The results showed that by adding the social network variables into the classification tree increase of 23.6% classification accuracy and application of Bagging techniques on single CART can improve the classification accuracy of 5.3%. The classification obtained some of the main characteristics of dropout students 7-17 years old in Sulawesi ie they are children who live in an environment that has quite high dropout rate, has a head of household who was not young anymore, and live with brother who also dropped out of school.id
dc.language.isoidid
dc.publisherBogor Agricultural Universityid
dc.subject.ddcStatisticsid
dc.subject.ddcStatistical analysisid
dc.subject.ddc2015id
dc.subject.ddcSulawesiid
dc.titleKlasifikasi Anak Putus Sekolah dengan Melibatkan Peubah Jaringan Sosial Menggunakan CART di Sulawesiid
dc.typeThesisid
dc.subject.keywordclassification of dropout studentid
dc.subject.keywordclassification and regression trees (CART)id
dc.subject.keywordbootstrap aggregating (Bagging)id
dc.subject.keywordaccuracy of classification rateid
Appears in Collections:MT - Mathematics and Natural Science

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