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All Journal Geo Media: Majalah Ilmiah dan Informasi Kegeografian J SIG (Jurnal Sains Informasi Geografi) Jurnal Geografi LIngkungan Tropik (Journal of Geography of Tropical Environments)
Suastini, Ni Made Mega Melliana
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Energy Environmental Science

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COMPARISON RESULT FOR THE PREDICTION ACCURACY OF SEAWATER INTRUSION BASED ON DIFFERENT SAMPLE SIZES AND LAND COVER CHARACTERISTICS USING INVERSE DISTANCE WEIGHTING AND KRIGING Suastini, Ni Made Mega Melliana; Ghazali, Mochammad Firman; Dermawan, Ananda; Salsabila, Choirunnisa; Zahra, Lauditta; Aulia, Mila
Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments)
Publisher : UI Scholars Hub

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Abstract

This study aims to determine seawater intrusion (SWI) based on sample sizes' contribution to land cover characteristics' accuracy using inverse distance weighting (IDW) and Kriging. The SWI is explained based on the extracted salt concentration from the dissolved soil. Here, this study used 24 samples of salt concentration, namely salinity samples collected by systematic random sampling and divided into two groups: ground control points (GCP) and independent checkpoints (ICP). Two interpolation methods, namely IDW and Kriging, are used to make a spatial prediction of the SWI, and their results are evaluated based on their accuracy by observing the root mean square error (RMSE). Based on the results of the best interpolation method using various sample size scenarios considering the knowledge to consider sufficient samples for SWI estimation, namely, the Kriging method produces the lowest RMSE value of 0.011 in model 1 and the highest RMSE value of 0.025 in model 3. The kriging method does not work well if the sample number is small. Compared to IDW, which has the highest RMSE value of 0.028 in model 3 and the lowest RMSE value of 0.13, respectively, in model 1. At the same time, the IDW method can work well even though the sample size is small. However, both interpolation methods are suitable for detecting seawater intrusion in Way Urang Village. In this study also, land cover affects the dynamics of salt concentration so that open land may have a higher salinity value than shrubs and vegetation with low salinity values causing the soil in Way Urang Village not to be polluted by seawater intrusion because the salinity concentration does not exceed the limit.
MEMILIH KANAL CITRA SENTINEL 2 TERBAIK UNTUK DETEKSI INTRUSI AIR LAUT DI KELURAHAN WAY URANG Aulia, Mila; Ghazali, Mochamad Firman; Dermawan, Ananda; Salsabila, Choirunnisa; Zahra, Lauditta; Suastini, Ni Made Mega Melliana
J SIG (Jurnal Sains Informasi Geografi) Vol 6, No 1 (2023): Edisi Mei
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/jsig.v6i1.1594

Abstract

The phenomenon of sea water intrusion almost occurs in all coastal areas. This phenomenon occurs scientifically and non-scientific which can lead to reduced groundwater quality. Utilization of remote sensing images, such as Sentinel 2 can be used to map the distribution of seawater intrusion in Way Urang Urban Village, South Lampung Regency. It just needs to be preceded by choosing the right band. Therefore, the statistical test process in the form of regression needs to be considered. The data needed include seawater intrusion in the field in the form of 18 sample points and Sentinel 2 Satellite Imagery. Based on the results of the regression test, bands 9, 10, 11, and 12 are bad bands with an R2 value of 0.0032-0.0624, bands 1, 6, 7, 8, 8A with an average value of R2 0.1171-0.0624 is a poor band, and bands 2, 3, 4, especially band 5 with R2 0.2099-0.3483 are the best bands in mapping the distribution of seawater intrusion. However, the Root Mean Square Error (RMSE) value of band 8A is 0.2570 which is smaller than band 5 which is 0.4335. So it can be said that band 5 is the best in mapping seawater intrusion with the highest R2 value. But if we look at the RMSE value, band 8A has better accuracy than band 5.
Model Regresi Spasial untuk Pendugaan Intrusi Air Laut Berdasarkan Relasi Pengukuran Salinitas terhadap Vegetation Soil Salinity Index Dermawan, Ananda; Ghazali, Mochamad Firman; Salsabila, Choirunnisa; Zahra, Lauditta; Aulia, Mila; Suastini, Ni Made Mega Melliana
Geomedia Majalah Ilmiah dan Informasi Kegeografian Vol. 21 No. 1 (2023): Geo Media: Majalah Ilmiah dan Informasi Kegeografian
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/gm.v21i1.51901

Abstract

Intrusi air laut di wilayah pesisir sering menjadi permasalahan bagi lingkungan sekitarnya sehingga perlu dilakukan upaya untuk mengidentifikasi keberadaan intrusi tersebut. Hal ini dapat dinilai menggunakan teknologi penginderaan jauh. penelitian ini dilakukan dengan menganalisis Citra Satelit Sentinel-2, data salinitas dari pengukuran lapangan, dan perhitungan statistik. Salinitas tanah akan diperkirakan menggunakan vegetation soil salinity index (VSSI). Penelitian ini mengintegrasikan data pengukuran salinitas lapangan dengan VSSI untuk membangun model persamaam regresi linear dan nonlinear. Ada tiga model regresi yang digunakan yaitu regresi linear, regresi eksponensial, dan regesi polynomial. Analisis ketiga model tersebut menunjukkan bahwa regersi polynomial merupakan model yang paling sesuai untuk estimasi salinitas berdasarkan VSSI dengan nilai koefisien determinasi (R2) 11,04%. Hasil estimasi salinitas berdasarkan VSSI menggunakan model polynomial memiliki koreasi yang cukup baik terhadap observasi salinitas dengan nilai koefisien determinasi (R2) 42,49%, sedangkan validasi estimasi tersebut memiliki akurasi cukup tinggi dengan nilai RMSE 0,0013% dan MAE 0,0011%. Kata kunci : Intrusi air laut, Salinitas, Analisis regresi, Sentinel-2, VSSI
Co-Authors Aulia, Mila Dermawan, Ananda Ghazali, Mochamad Firman Ghazali, Mochammad Firman Salsabila, Choirunnisa Zahra, Lauditta