PENGEMBANGAN ANALISIS GEROMBOL BERHIRARKI DENGAN KETERGANTUNGAN SPASIAL PADA INDIKATOR MAKRO SOSIAL EKONOMI DI KABUPATEN/KOTA PROVINSI SULAWESI TENGAH

  • Iman Setiawan Statistics Studies Program, Tadulako University (Untad), Indonesia
  • Nur’eni Nur’eni Statistics Studies Program, Tadulako University (Untad), Indonesia
  • Sritasarwati Putran Statistics Studies Program, Tadulako University (Untad), Indonesia
Keywords: hierarchical clustering, macro social economic indicator, principal component analysis, spatial dependency distance

Abstract

This paper develops how the hierarchical clustering analysis uses multivariate variables with spatial dependence on macro social-economic indicator data in Regency/City Central Sulawesi Province. Macro social-economic indicator data used in this paper are the number of criminal cases, per capita expenditure, population density, and Human Development Index of Regency/City of Central Sulawesi Province in 2018. To answer this question, Macro social-economic indicator data was reduced to a new variable using principal component analysis. The new variable was used to identify spatial dependency using the Moran index test. Spatial weight, that meets the Moran index test on the alternative hypothesis (there is a spatial dependency between locations), was used as the spatial dependency distance. Cluster analysis using two distance including variable and spatial dependency distance. The results showed that neighboring Regency/City are in the same cluster (spatial dependency occasion). So that there are five clusters Regency/City in Central Sulawesi Province.

References

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[BPS] Badan Pusat Statistik Provinsi Sulawesi Tengah. (2019). Indikator Makro Ekonomi Provinsi Sulawesi Tengah Triwulan I Tahun 2019. Palu (ID): Badan Pusat Statistik Provinsi Sulawesi Tengah.

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Published
2020-02-28
Section
Articles