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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA)
Ali Mas'ud Dwi Cahyo
Institut Pertanian Bogor
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Materials Science & Nanotechnology Physics

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Meningkatkan model deteksi estimasi distribusi musiman padatan tersuspensi total di perairan Selat Madura, Indonesia Ali Mas'ud Dwi Cahyo; Ario Damar; Fery Kurniawan; Adrian Hidayat
Jurnal Penelitian Pendidikan IPA Vol 10 No 11 (2024): November
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i11.8605

Abstract

High TSS causes siltation around coastal areas in the Madura Strait. TSS impacts water quality and habitat health. It's necessary to know that TSS distribution can vary each season. The algorithm detects TSS distribution by processing Landsat-8 satellite image data. However, existing algorithms are sometimes only suitable for some instances, so the results do not correspond to actual conditions. Therefore, this paper wants to build a better detection model using Laili's algorithm to determine whether satellite image analysis can explain the exact conditions. Laili's algorithm detection was validated and corrected against field data via a correlation test. It’s necessary to know the spatial distribution pattern of data attribute values using the Moran Index. The results TSS in the dry season is 5-18 mg/L and covers an area of up to 4 km; in the rainy season, it is 5-22 mg/L and can cover an area of up to 7.8 km. Moran's Index results show that spatial autocorrelation in the distribution pattern results in a cluster pattern. These results show that the detection model is relatively reasonable and can be used as training data to detect the distribution of TSS in the Madura Strait in subsequent years.
Co-Authors Adrian Hidayat Ario Damar FERY KURNIAWAN