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All Journal Geo Media: Majalah Ilmiah dan Informasi Kegeografian Jurnal Keteknikan Pertanian Forum Geografi MAJALAH ILMIAH GLOBE Spatial : Wahana Komunikasi dan Informasi Geografi Jurnal SIAR ILMUWAN TANI
Slamet Suprayogi
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Education

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Journal : Forum Geografi

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Contamination Vulnerability Analysis of Watershed for Water Quality Monitoring Widyastuti Widyastuti; Slamet Suprayogi
Forum Geografi Vol 20, No 1 (2006): July 2006
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v20i1.1803

Abstract

This research is an early step to determine the location of rain gauge station for artificial neural network modeling. The implementation of this model is very useful for water quality monitoring. The objectives of this study are: 1) to study the distribution of watershed parameter, that are average annual precipitation, land use and land-surface slope, 2) to conduct vulnerability analysis of watershed contamination, 3) to determine the location of rain gauge station. The study was performed by weighing and rating method of watershed parameters. The vulnerability degree of watershedtocontaminationispresentedasvulnerabilityindex.Thisindexisdeterminedbyoverallsumofallmultiplication between score and weigh number of each parameter. All data manipulation and data analysis were performed by using Geographic Information System (ArcView version by 3.2). The vulnerability of watershed contamination map had been generated using overlay operation of parameters. The results show that vulnerability index are varies between 10 up to 40 intervals. Hence, the indexes were categorized into three levels of watershed vulnerability, namely low (10 – 20), moderate (20 – 30) and high (30 – 40). It is found that the study area covered more by high vulnerability of watershed to contamination. The zoning of watershed vulnerability meant to determine the rain gauge location. There are three rain gauge stations on the area that they are in a high vulnerability level, whereas the other vulnerability level area has one rain gauge station. Each level of vulnerability area is able to represent the source of contaminant that it maybe influence the water quality of Gajahwong river.
Estimation of Solar Radiation using Artificial Neural Network Slamet Suprayogi
Forum Geografi Vol 18, No 1 (2004)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v18i1.602

Abstract

The solar radiation is the most important fator affeccting evapotranspiration, the mechanism of transporting the vapor from the water surface has also a great effect. The main objectives of this study were to investigate the potential of using Artificial Neural Network (ANN) to predict solar radiation related to temperature. The three-layer backpropagation were developed, trained, and tested to forecast solar radiation for Ciriung sub Cachment. Result revealed that the ANN were able to well learn the events they were trained to recognize. Moreover, they were capable of effecctively generalize their training by predicting solar radiation for sets unseen cases.
Co-Authors agung Suryanto Ahmad Cahyadi **) Andy Wibawa Nurrohman Bokiraiya Latuamury Budi Indra Setiawan Deby Putri Christianingsih Febriana Irfani Hendy Fatchurohman LILIK BUDIPRASETYO M. Zohri Margaretha Widyastuti Muhammad Junaidi Nasril Hanan Rizki Hendriawan Shinta Wahyu Ningsih Sudarmadji Sudarmadji Suhd Tannia Rosali Oktaviani Widyastuti Widyastuti