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All Journal Indonesian Journal of Geography Ecotrophic, Journal of Environmental Science Media Komunikasi Geografi Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Majalah Geografi Indonesia Journal of Degraded and Mining Lands Management Forum Geografi GEA, Jurnal Pendidikan Geografi JURNAL SWARNABHUMI J SIG (Jurnal Sains Informasi Geografi) JURNAL GEOGRAFI Geografi dan Pengajarannya Jurnal Aplikasi dan Inovasi Iptek (JASINTEK)
Slamet Suprayogi
Departemen Geografi Lingkungan, Fakultas Geografi, Universitas Gadjah Mada, Yogyakarta 55281
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Environmental Science Physics Social Sciences Other

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Journal : Forum Geografi

 1 
Estimation of Solar Radiation using Artificial Neural Network Suprayogi, Slamet
Forum Geografi Vol 18, No 1 (2004)
Publisher : Forum Geografi

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

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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 Suprayogi, Slamet
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.
Contamination Vulnerability Analysis of Watershed for Water Quality Monitoring Widyastuti, Widyastuti; Suprayogi, Slamet
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.
Distribution of Accuracy of TRMM Daily Rainfall in Makassar Strait Giarno, G; Hadi, Muhammad Pramono; Suprayogi, Slamet; Murti, Sigit Heru
Forum Geografi Vol 32, No 1 (2018): July 2018
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v32i1.5774

Abstract

This research aims to evaluate rainfall estimates of satellite products in regions that have high variations of rainfall pattern. The surrounding area of Makassar Strait have chosen because of its distinctive rainfall pattern between the eastern and western parts of the Makassar Strait. For this purpose, spatial distribution of Pearson’s coefficient correlation and Root Mean Square Error (RMSE) is used to evaluate accuracy of rainfall in the eastern part of Kalimantan Island and the western part of Sulawesi Island. Moreover, we also used the contingency table to complete the parameter accuracy of the TRMM rainfall estimates. The results show that the performance of TRMM rainfall estimates varies depending on space and time. Overall, the coefficient correlation between TRMM and rain observed from no correlation was -0.06 and 0.78 from strong correlation. The best correlation is on the eastern coast of South West Sulawesi located in line with the Java Sea. While, no variation in the correlation was related to flatland such as Kalimantan Island. On the other hand, in the mountain region, the correlation of TRMM rainfall estimates and observed rainfall tend to decrease. The RMSE distribution in this region depends on the accumulation of daily rainfall. RMSE tends to be high where there are higher fluctuations of fluctuating rainfall in a location. From contingency indicators, we found that the TRMM rainfall estimates were overestimate. Generally, the absence of rainfall during the dry season contributes to improving TRMM rainfall estimates by raising accuracy (ACC) in the contingency table.
SUITABLE PROPORTION SAMPLE OF HOLDOUT VALIDATION FOR SPATIAL RAINFALL INTERPOLATION IN SURROUNDING THE MAKASSAR STRAIT Giarno, Giarno; Hadi, Muhammad Pramono; Suprayogi, Slamet; Murti, Sigit Heru
Forum Geografi Vol 33, No 2 (2019): December 2019
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v33i2.8351

Abstract

Spatial rainfall interpolation requires a number of suitable validation samples to maintain accuracy. Generally, the larger the areas which can be predicted, the better the interpolation. In addition, the data used for validation should be separated from the modelling data. Moreover, the number of samples determine optimally proportion the independent sites. The objective of this study is to determine the optimal sample ratio for holdout validation in interpolation methods; the Makassar Strait was chosen as the study location because of its daily rainfall variation. The accuracy of the sample selection is tested using correlation, root mean square error (RMSE), mean absolute error (MAE) and the indicators of contingency tables. The results show that accuracy depends on the ratio of the modelling data. Therefore, the more extensive the data used for interpolation, the better the accuracy. Otherwise, if the rain gauge data is separated according to province, there will be a variation in accuracy in the portion of independent samples. For rainfall interpolation, it is recommended to use a minimum 75% of data sites to maintain accuracy. Comparison between kriging and inverse distance weighting or IDW methods indicates that IDW is better. Moreover, rainfall characteristics affect the accuracy and portion of the independent sample.
Co-Authors agung Suryanto Alvia, Sakila Andung Bayu Sekaranom Andy Wibawa Nurrohman Aris Sutardi Arno, Giarno Azura Ulfa, Azura Bokiraiya Latuamury Budi Indra Setiawan Christanto, Nugroho Dwi Agustina Edhy Martono, Edhy Eko Ali Saputro Eko Sugiharto Evi Mivtahul Khoirullah, Evi Mivtahul Fadilah, Gita Oktaviani Fadlillah, Lintang Nur Fatchurohman, Hendy Forita Dyah Arianti, Forita Dyah Giarno Giarno Hadi, Mohammad Pramono Hajar, St. Hanan, Nasril Hendriawan, Rizki Hermantoro . Hermawan, Sekar Gading Hidayah, Kuny Ig. L. Setyawan Purnama Iman, Atifatul Imroatush shoolikhah Irfani, Febriana Iwuk Sri Lestari Izzati, Amaeliya Julianti Marbun La Musa M Pramono Hadi, M Pramono M Widyastuti M. Widyastuti Margaretha Widiyastuti Margaretha Widyastuti Mohammad Pramono Hadi Muhammad Faris, Muhammad Muhammad Ngainul Malawani Muhammad Pramono Hadi, Muhammad Pramono Musafir Ningsih, Shinta Wahyu Nunik Cokrowati Nur Aziz Widodo Oktaviani, Tannia Rosali Prihantarto, Wikan Jaya Rafif, M. Roid Al Rahmawati, Laelina Ramadhani, Endi Raras Endarto Rudiyanto Rudiyanto Saputro, Eko Ali Sa’ban, M. Iman Nichfu Setiawan, Bagus Arif Setyawan Purnama Setyawan Purnama Sigit Heru Murti Sofia Wantasen Soliyanti Sudarmadji Sudarmadji Sudarmadji Sudarmadji Sudarmadji Sudarmadji Suhdi, Suhdi Suhendri, Salwa Suratman Suratman Suroso Suroso Suroso Tivianton, Tommy Andryan Tjahyo Nugroho Adji Totok Gunawan Totok Gunawan Totok Gunawan Totok Gunawan Totok Gunawan Widayati Indarsih Widyastuti Widyastuti Zohri, M.