PENGELOMPOKAN RUMAH TANGGA MISKIN DI KECAMATAN TABIR BARAT MENGGUNAKAN METODE LATENT CLASS CLUSTER ANALYSIS

  • Irtania Muthia Rizki Departemen Statistika, Fakultas MIPA, Universitas Padjadjaran
  • Septiadi Padmadisastra Departemen Statistika, Fakultas MIPA, Universitas Padjadjaran
  • Bertho Tantular Departemen Statistika, Fakultas MIPA, Universitas Padjadjaran

Abstract

Poverty is one of the problems that becomes concern in all countries. In Indonesia, one of the provinces that has high poverty rates is Jambi (9.12% in 2015).
Result of coordination meeting of all Camat in Jambi Province, reported that the Tabir Barat is the poorest sub-district. The condition is caused mostly by inadequate household infrastructure. Therefore it is necessary for grouping households based on the household infrastructure condition to find the household groups which should be prioritized in the development of poverty alleviation. To describe the poverty variable based on household infrastructure, Bappeda uses 9 indicators, that are residential building status, the widest type of floor, the widest type of wall, the widest type of roof, drinking water source, defecation facility, stool drainage, main lighting and cooking fuel. Because of the folowing reasons: the poverty is an unmeasurable latent variable, and indicators of poverty are categorial variables, the Latent Class Cluster analysis were used in this research as a grouping method. The result shows that there are 5 clusters / latent classes
with their respective characteristics of the household in the Tabir Barat.

Published
2017-12-29
How to Cite
RIZKI, Irtania Muthia; PADMADISASTRA, Septiadi; TANTULAR, Bertho. PENGELOMPOKAN RUMAH TANGGA MISKIN DI KECAMATAN TABIR BARAT MENGGUNAKAN METODE LATENT CLASS CLUSTER ANALYSIS. Jurnal Ilmiah Matematika dan Pendidikan Matematika, [S.l.], v. 9, n. 2, p. 63-74, dec. 2017. ISSN 2550-0422. Available at: <http://jos.unsoed.ac.id/index.php/jmp/article/view/2867>. Date accessed: 01 feb. 2023. doi: https://doi.org/10.20884/1.jmp.2017.9.2.2867.

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