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All Journal Jurnal Mahasiswa Statistik Inferensi
pramoedyo, henny
brawijaya university
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics Social Sciences

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PEMODELAN GEOGRAPHICALLY WEIGHTED POISSON REGRESSION (GWPR) DENGAN FUNGSI PEMBOBOT ADAPTIVE BISQUARE DAN TRICUBE KERNEL (Studi Kasus Angka Kematian Ibu di Jawa Timur tahun 2012) NOVIANINGRUM, RULLIANTI; pramoedyo, henny
Jurnal Mahasiswa Statistik Vol 3, No 4 (2015)
Publisher : Jurnal Mahasiswa Statistik

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PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION DENGAN PEMBOBOT TRICUBE KERNEL (STUDI KASUS ANGKA HARAPAN HIDUP DI PROVINSI JAWA TIMUR TAHUN 2012) Aljaza, Hanafi Rahman; pramoedyo, henny
Jurnal Mahasiswa Statistik Vol 3, No 4 (2015)
Publisher : Jurnal Mahasiswa Statistik

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PENENTUAN FAKTOR-FAKTOR YANG MEMPENGARUHI ANGKA PARTISIPASI SEKOLAH MENGGUNAKAN GEOGRAPHICALLY WEIGHTED REGRESSION DENGAN METODE STEPWISE Dewi, Vita Rosiana; astutik, suci; pramoedyo, henny
Jurnal Mahasiswa Statistik Vol 3, No 2 (2015)
Publisher : Jurnal Mahasiswa Statistik

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PENGGUNAAN METODE AVERAGE DIFFERENCE ALGORITHM UNTUK MENDETEKSI SPATIAL OUTLIER PUSPITA, CICI LIA; pramoedyo, henny
Jurnal Mahasiswa Statistik Vol 3, No 3 (2015)
Publisher : Jurnal Mahasiswa Statistik

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MODEL GEOGRAPHICALLY WEIGHTED REGRESSION SEMIPARAMETRIC (GWRS) DENGAN FUNGSI PEMBOBOT TRICUBE PADA DATA KEMISKINAN DI JAWA TIMUR TAHUN 2011 Anam, Shilahul; pramoedyo, henny
Jurnal Mahasiswa Statistik Vol 3, No 4 (2015)
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Spatio-Temporal Kriging for Monthly Precipitation Interpolation in East Kalimantan Jannah, Friendtika Miftaqul; Fitriani, Rahma; Pramoedyo, Henny
Inferensi Vol 8, No 2 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i2.22195

Abstract

Precipitation is one of the factors that can lead to various disasters, such as droughts and floods. Ordinary interpolation methods, such as spatial kriging, cannot accommodate the time element, which is crucial for addressing precipitation-related disasters. Therefore, this study applies a spatio-temporal kriging, which incorporates both spatial and temporal elements. The aim of this study is to develop a spatio-temporal kriging model for precipitation, serving as a basis for interpolating precipitation at unobserved points over various time intervals within the study domain. This model is expected to be an effective tool for disaster mitigation and water conservation strategies. The data used in this study comprises total monthly precipitation recorded at seven precipitation observation posts in East Kalimantan from 2021 to 2023. The findings indicate that the spatio-temporal ordinary kriging model is the most suitable approach, with the best semivariogram model identified as the simple sum-metric. The spatial semivariogram follows an exponential model, while the temporal and joint semivariograms follow Gaussian models. The accuracy of the chosen model yields an RMSE of 2493.687. The interpolation results reveal that West Kutai falls within the medium to high precipitation category, making it the district with the highest flood risk.
Co-Authors Aljaza, Hanafi Rahman Anam, Shilahul Dewi, Vita Rosiana Jannah, Friendtika Miftaqul NOVIANINGRUM, RULLIANTI PUSPITA, CICI LIA Rahma Fitriani Suci Astutik