Analisis Spasial Persebaran Dan Pemetaan Kerawanan Daerah Titik Panas Di Kalimantan Timur Menggunakan Spatial Pattern Analysis Dan Flexibly Shaped Spatial Scan Statistic

  • Tiara Nur Hikmaulida
  • Memi Nor Hayati Jurusan Matematika, Prodi Statistika, Universitas Mulawarman
  • Sri Wahyuningsih Jurusan Matematika, Prodi Statistika, Universitas Mulawarman

Abstract

The statistical method used to analyze spatial data and spatial statistics. The case study in this study is the average number of hotspots in East Kalimantan by Regency / City in 2016-2018. This study aims to analyze the presence or absence of spatial autocorrelation in the data on the number of hotspots, determine the distribution pattern of hotspots, as well as determine the level of vulnerability of potential areas for forest and land fires in East Kalimantan by Regency / City in 2016-2018.  The method used to analyze spatial autocorrelation globally and determine the distribution patterns is the Moran Index. Local Indicator of Spatial Autocorrelation (LISA) to analyze spatial autocorrelation locally. Spatial autocorrelation analysis results globally using the Moran Index with α = 25% shows that there is a spatial autocorrelation in the average number of hotspots in East Kalimantan in 2016-2018. The distribution pattern of hotspots in East Kalimantan is the pattern of spread which shows that in 2016-2018 the hotspots spread in each district / city of East Kalimantan. Meanwhile, the results of the local analysis using LISA showed that there were spatial autocorrelations in several districts / cities in East Kalimantan. The method used to determine the level of vulnerability of potential forest and land fires is Flexibly Shaped Spatial Scan Statistics and LISA. The results showed that the regencies / cities included in the category of forest and land fire hazard were Samarinda City, Bontang City, Kutai Kartanegara District and East Kutai.

Downloads

Download data is not yet available.

References

[1] Banerjee, S., Carlin, B.P, and Gelfand, A.E. (2004). Hierarchical Modeling and Analysis for Spatial Data. Boca Raton: Chapman and Hall/CRC.
[2] Lee, J., dan Wong, D.W.S. (2001). Statistical Analysis with ArcviewGIS. United Stated of America: John Wiley & Sons, Inc.
[3] Tango, T. dan Takahashi, K. (2005). A Flexibly Shaped Spatial Scan Statistic for Detecting Clusters. International Journal Health Geographics. vol. 4, no.11, 2005.
[4] Arifin, N. (2018). Hutan Indonesia Sebagai Paru-Paru Dunia di Masa Depan. https://www.goodnewsfromindonesia.id/2018/01/12/bagaimana-hutan-indonesia-sebagai-paru-paru-dunia-di-masa-depan. Diakses pada 22 Januari 2019.
[5] Akbar, A. (2008). Pengendalian kebakaran hutan berbasis masyarakat sebagai suatu upaya mengatasi risiko dalam REDD. Jurnal Tekno Hutan Tanaman Vol 1(1);11-22. Kalimantan Selatan: Balai Penelitian Kehutanan Banjarbaru.
[6] Ekadinata, A. Dewi, S. Hadi, D.P. Nugroho, D.K. Johana, F. (2011). Sistem Informasi Geografi. Malang: PT Bumi Pertiwi
[7] Ludwig, J.A, dan J.F. Reynolds. (1988). Statistical Ecology. Canada: John Wiley and Sons, Inc.
[8] Lembaga Penerbangan dan Antariksa Nasional (LAPAN). (2016). Informasi Titik Panas (Hotspot) Kebakaran Hutan dan Lahan. ISBN 978-602-96352-2-5.
Published
2020-07-19
How to Cite
HIKMAULIDA, Tiara Nur; HAYATI, Memi Nor; WAHYUNINGSIH, Sri. Analisis Spasial Persebaran Dan Pemetaan Kerawanan Daerah Titik Panas Di Kalimantan Timur Menggunakan Spatial Pattern Analysis Dan Flexibly Shaped Spatial Scan Statistic. Progressive Physics Journal, [S.l.], v. 1, n. 1, p. 20-28, july 2020. ISSN 2722-7707. Available at: <https://jurnal.fmipa.unmul.ac.id/index.php/ppj/article/view/615>. Date accessed: 27 apr. 2024. doi: https://doi.org/10.30872/ppj.v1i1.615.