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All Journal Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Indonesian Journal of Statistics and Its Applications
nurrusydah, zaima
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Mathematics Medicine & Pharmacology Other

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PENERAPAN FLEXIBLE SPACE TIME SCAN STATISTICS UNTUK MENGIDENTIFIKASI HOTSPOT TUBERKULOSIS nurrusydah, zaima; Mila Dewi, Ni Putu Ayu
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 8 No 2 (2020): Volume 8 Nomor 2
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v8i2.16065

Abstract

Tuberculosis (TB) merupakan kedaruratan global yang sampai saat ini belum teratasi. Menurut Global Tuberculosis Report 2019, Indonesia menjadi negara dengan kasus TB tertinggi kedua di dunia. Jumlah kasus TB terbanyak di Indonesia berada di Provinsi Jawa Barat. Demi kemajuan program eliminasi TB di Indonesia, maka layanan TB berbasis wilayah sangat diperlukan. Dengan melakukan identifikasi hostpot TB, prioritas untuk menjangkau populasi yang beresiko tinggi dapat dilakukan. Flexible Space Time Scan Statistic (STSS) merupakan salah satu metode analisis spatiotemporal yang mampu mengidentifikasi hotspot TB. Penelitian ini menerapkan Flexible STSS pada kabupaten Bogor yang pada tahun 2018 memiliki jumlah penderita TB terbanyak dibandingkan kabupaten/kota lainnya di Provinsi Jawa Barat. Hasil analisis menunjukkan lima hotspot TB di wilayah kabupaten dan kota Bogor yang sebagian besar tersebar di bagian barat Kabupaten Bogor. Kecamatan Leuwiliang, Leuwisadeng, Cibungbulang, Ciampea, Cigudeg, Nanggung, dan Sukajaya selain memiliki kecenderungan yang tinggi untuk menjadi hotspot TB juga memiliki resiko peningkatan terjadinya TB yang tinggi.
PENERAPAN CYLINDRICAL DAN FLEXIBLE SPACE TIME SCAN STATISTIC DALAM MENGIDENTIFIKASI KANTONG KEMISKINAN DI PULAU JAWA TAHUN 2011-2015 Nurrusydah, Zaima; Erfiani, Erfiani; Sartono, Bagus
Indonesian Journal of Statistics and Applications Vol 3 No 2 (2019)
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.v3i2.274

Abstract

The Indonesian government formed the National Team for the Acceleration of Poverty Reduction (TNP2K) to eradicate poverty. TNP2K requires identification of priority areas or poverty hotspots so that the program can be targeted. Scan statistic is one of the most widely used methods to identify poverty hotspots. Cylindrical STSS uses cylindrical scanning windows while most geographical areas are not circular. Flexible STSS is able to detect poverty hotspots in a flexible form. This study aims to identify poverty hotspots using Cylindrical and Flexible STSS then compare the results of both and then determine the best STSS method. Cylindrical STSS tends to have wider hotspots than Flexible STSS. There are a number of districts that are not eligible to be included as poverty Flexible STSS is able to produce better poverty hotspots by not including these districts Poverty hotspots produced by Flexible STSS have higher LLR values. The more suitable STSS method has optimal K values and high suitability with TNP2K priority areas. Cylindrical STSS has an optimal K value when K = 8 and 9. Flexible STSS has a constant LLR value. Flexible STSS has a higher LLR value than Cylindrical STSS at each K value. Flexible STSS with K = 9 has optimal K and high suitability with TNP2K priority areas so that it is the more suitable STSS method to identify poverty hotspots in Java.
Co-Authors Bagus Sartono Erfiani Erfiani Mila Dewi, Ni Putu Ayu