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Journal : JURNAL POLI-TEKNOLOGI

Studi Stabilitas Tanah Ekspansif dengan Penambahan Pasir untuk Tanah Dasar Konstruksi Jalan Sutikno Sutikno; Denny Yatmadi
Jurnal Poli-Teknologi Vol. 9 No. 1 (2010)
Publisher : Politeknik Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (316.886 KB) | DOI: 10.32722/pt.v9i1.479

Abstract

Abstract Problems of ekspansive soil is stability (CBR) and swelling effect of process of compaction. One of the soil expansive component in general is sand beside silt and clay, added sand will make composition of clay to downhill expansive soil. With condensation process conducted by mixing of sand to ekspansive soil with addition composition equal to 10%, 20%, 30%. and 35% to dry weight of ekspansive soil. Conclusion which in earning: Level of CBR mount above ekspansive soil of genuiness come up with the condition of addition of sand counted 30% to the condition of soaked, while at addition of sand up to 35%, value of CBR (downhill stabilitation) but still above original ekspansive soil value, at addition of sand up to 35%, value of CBR (downhill stabilitation) but still above original ekspansive soil value. For the development of (ekspansive soil swelling) of ekspansive soil with addition of sand, condition of natural swelling of value and reduction isn't at addition of sand between 10 to 30% and lower at addition of sand counted 35%. There are influence of addition of sand at ekspansive soil compacted to stability (CBR) and swelling of ekspansive natural of change which are positive after mixed with sand, tired optimasi at addition of sand between 20% up to 30%. Keyword : ekspansif soil, sand, condensation, stability
PERBANDINGAN MODEL CURAH HUJAN LIMPASAN ANTARA METODE JARINGAN SYARAF TIRUAN DENGAN METODE SACRAMENTO DENNY YATMADI; NUZUL BARKAH PRIHUTOMO
Jurnal Poli-Teknologi Vol. 13 No. 1 (2014)
Publisher : Politeknik Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/pt.v13i1.604

Abstract

ABSTRACT The rainfall-runoff modeling is needed to fill in the data or make the data longer. Some method can be used for forecast rainfall processing or runoff like sacramento or artificial neural network (ann). The ann is one of artificial intelligent that is an artificial representation of human’s brain which always try to simulation learning process of its. This model is a black box model, so implementation did not need complect science between many aspects in rainfall-runoff happened process. The case study on the upstream of citarum river basin (saguling dam). The data used are a rainfall data (11 rain station) , inflow and sediment rate of month during 19 years from 1986 up to 2004. Rainfall data is input and inflow rate is target output. This research use sacramento and reduced gradient method. The result for training step sacramento’s method the correlation is 81 % and reduced gradient’s method the correlation is 99 %. For testing sacramento ‘s method the correlation is 83.22 % and reduced gradient’s method alternative 2 with four hidden node gives the correlation is 65.57 %. For the next step especially the artificial neural network method still need improvement so that the artificial neural network can be used for modeling of rainfall runoff process. Keywords : rainfall runoff, sacramento, artificial neural network, hidden node, reduced gradient.