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All Journal Xplore: Journal of Statistics Indonesian Journal of Statistics and Its Applications
Indahwati
Department of Statistics, IPB University, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Other

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Analisis Gerombol Pautan Ward Kabupaten/Kota di Provinsi Jawa Timur Berdasarkan Indikator Kesejahteraan Rakyat annida marsa salsabila; Mohammad Masjkur; Indahwati
Xplore: Journal of Statistics Vol. 11 No. 3 (2022): Vol. 11 No. 3 (2022)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (301.711 KB) | DOI: 10.29244/xplore.v11i3.1024

Abstract

The main goal in the development of a country is to improve the welfare ofthepeople. One of the causes of the problems of people's welfare in Indonesia is that thedevelopment carried out by the government is not carried out evenly and not on target,not least in East Java Province. to group and look at the characteristics of 38regencies/cities in East Java Province based on people's welfare indicators sothat thegovernment in making policies can be evenly distributed and on target. Thisstudy useshierarchical cluster analysis. The data used is the welfare indicator data for 38districts/cities of East Java Province in 2019. The hierarchical cluster analysismethodused is the Ward method. The results of the study using dendogram cuts and the ratioof standard deviations within clusters and standard deviations betweenclusters showedthat districts/cities in East Java province could be divided into six clusters. In eachcluster, the characteristics are seen using the average value of eachvariable. Areas withvery good development are in cluster six and areas that requiremore development inmany aspects are in cluster five.
Study of Small Area Estimation when Nighttime Lights as an Auxiliary Information is Measured with Error: Kajian Pendugaan Area Kecil dengan Kesalahan Pengukuran pada Peubah Penyerta Nighttime Lights Ardi Surya; Indahwati; Erfiani
Indonesian Journal of Statistics and Applications Vol 8 No 1 (2024)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v8i1p47-57

Abstract

The need for accelerated development requires rapid data collection. In today's increasingly advanced technological landscape, the utilization of big data emerges as a highly reliable solution for data collection. One exemplary form of big data is the daily capture of satellite imagery, particularly nighttime lights (NTL). NTL serves as a valuable product derived from satellite imagery and can be employed as an alternative dataset for analysis. This research utilizes Nighttime lights as an auxiliary variable to estimate the average household per capita expenditure in small areas, namely districts, employing the empirical best linear unbiased prediction Fay Herriot (EBLUP FH) method and small area estimation by incorporating measurement error effects on the covariate (SAE-ME). The study demonstrates that Nighttime lights can be employed as an alternative auxiliary variable for estimating the average per capita expenditure in districts, as evidenced by a lower RRMSE compared to direct estimation results. However, the measurement error effects on the NTL covariate should be considered by employing a model that takes into account measurement errors. The SAE-ME method provides estimated average expenditure values at the district level that closely align with BPS publications, with an average RRMSE per district of 7.5 percent.
Co-Authors annida marsa salsabila Ardi Surya Erfiani Mohammad Masjkur