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Lilik Hendrajaya
Jurusan Fisika Kel.Fisika Bumi dan Sistem Kompleks, FMIPA, ITB Jl. Ganesha 10 Bandung 40132, Jawa Barat
Electrical & Electronics Engineering Energy Physics Other

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PREDIKSI VOLUME POTENSI LONGSORAN BERDASARKAN INVERSI RESISTIVITAS (Studi Kasus di Amahusu dan Erie Ambon) Matheus Souisa; Lilik Hendrajaya; Gunawan Handayani
PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Vol 5 (2016): PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) SNF2016
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (648.145 KB) | DOI: 10.21009/0305020404

Abstract

Investigations of landslides conducted intensive from year to year due to the intensity of the landslides that continues to increase along with the rainy season. This study aims to determine volume prediction of landslides through inversion resistivity of the subsurface in the area of the landslide. Research sites in the hills Amahusu and Erie District of Nusaniwe Ambon. Survey data retrieval using geoelectric resistivity with the Wenner-Schlumberger configuration and measurement is divided into several lines. The results of the study provide characterization of the landslide area slide-type rotation. The slip area of landslides is characterized by low resistivity and with layers of rock structure in the form of a layer of clay mixed with weathered rock and water-saturated clay layer. Predictive value of landslide volume when occurence the volume landslide for the location Amahusu of 70,953.9 m3 and Erie location of 34,042.3 m3, while the predictive value of the potential volume of landslides for the location Amahusu of 50,603.3 m3 and Erie location of 3,399.4 m3. The potential failure of a slope with a steep slope can predict occur of landslides subsequent in the original location. Keywords: landslides, volume prediction, inversion resistivity, slope failure.
Co-Authors Gunawan Handayani Matheus Souisa