Judul: IPB (Bogor Agricultural University)
Abstrak: One of the large rivers flowing in the center of Semarang City is Garang River with watershed area about 203 km2 and having characteristics such as high flood discharge and flash flood. The flash flood on January 25th 1990 caused more than 45 people died and goods loss was estimated to be 8.5 billion rupiahs. In this research, a flood early warning system is made, in which an automatic rainfall recorder (ARR) was placed in upstream of Garang River at sub district Gunungpati and an automatic water level recorder (AWLR) was placed in Simongan weir. To receive rainfall and water level data, a computer as server that is placed in Semarang government office. This also functions for sending flood status of Garang River (prepared/caution/careful) to flood attendants and stake holders. Beside that, artificial neural network (ANN) is used to predict water level in Garang River where the input are rainfall in upstream river for 1, 2, 3, 4 or 5 days before the occasion and the water level in the downstream for 3 hours before the occasion. The output is water level in downstream of Garang River for next 2 hours. This system is integrated with information technology that is SMS (Short Message Services) and Web so that the flood early warning can be accessed anywhere as long as communication network is available. The result of research, time for sending data of rainfall and water level telemetry system is less than 10 minutes, while information system that is built to give flood early warning information is less than 10 minutes. Consequently it fulfill in which the time to receive the information less than time when flood happened that is 2 hours. The result of optimum predicting during the ANN training is model 4 with 20 neurons; speed training 0.9 and momentum 0.3 which the input rainfall are four days before the occasion and the water level are 3 hours before the occasion having MSE 0.0046. Finally, the results of survey to flood attendants and staffs from government show that 86 % of the respondent that they absolutely need the flood early warning system.
Keyword: Automatic Rainfall Recorder (ARR), Artificial Neural Network (ANN), Flood Early Warning, Automatic Water Level Recorder (AWLR)

Judul: Pemetaan kawasan berpotensi banjir menggunakan sistem informasi georafis
Abstrak: Remote Sensing and Geographic Information System (GIS) can be applied to identify potential flood area. Remote Sensing helps to extract information without direct interaction with the object. On the other hand, GIS can be used to identify flood prone of an area using overlay method toward the parameters that causes flood phenomena. The object of this research was to mapping the vulnerability of flood area in Indramayu Regency using cartography models of biophysics parameters, to study the distribution and characteristic of flood area in Indramayu Regency, and to study the result using different rainfall parameters and weight category for mapping vulnerable flood area in Indramayu Regency. Data processing was done using software such as ArcView 3.3, ERDAS Imagine 9.1, and Frame & Fill (USGS). The used data are rainfall, Landsat Imagery; DEM, SRTM data; soil map, river map, and landform map. The methods consist of imagery analysis, DEM data analysis, rainfall data analysis, attribute data analysis, spatial analysis dan vulnerabilty class analysis. Rainfall parameter divided into two groups, the first group used annual mean rainfall data and the second group used monthly mean rainfall data (threemonth peak of rainy season). Proportion of parameters that called as a weight category in this research divided into two groups, the first group with different weight and the second group with equal weight. The results showed that Indramayu Regency can be concluded as a potential flood area, where the north side of Indramayu Regency is more vulnerable rather than the south side. The land characteristic of the potential flood area are flat area, alluvial plains, bad drainage, and paddy field land cover. The map that using monthly mean rainfall data and different weight is more representative for mapping flood area in Indramayu Regency.
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Judul: Penentuan Nilai Eigen dan Vektor Eigen dari Matriks Tridiagonal 2-Toeplitz dengan Pendekatan Polinomial Chebyshev
Abstrak: The eigenvalues and eigenvectors of a matrix can be determined by finding its characteristic polynomials. The characteristic polynomials of a tridiagonal 2-Toeplitz matrix is shown to be closely connected to polynomials which satisfy the Chebyshev recurrence relationship. If the order of the matrix is odd, then the eigenvalues are found explicitly in terms of the Chebyshev zeros and the eigenvectors are found in terms of the polynomials satisfying the recurrence relationship. For even ordered matrices, the situation is more complicated. The problem in these cases is that although the Chebyshev recurrence formula is still applied, its initial values are not generating Chebyshev polynomials
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