Flooding in Citarum always happens in Bandung District which causes loss of property, household damage, diseases moreover decease. The government provides aid for flood victims, but the help is not cover losses. In this circumstance, people need insurance. This study aims to set up flood insurance based on economic conditions, areas, and losses due to flooding. To find out the conditions, interviewed the village chief of Baleendah. The analytical methods used are linear regression analysis and analysis method mix. Linear regression analysis was used to estimate flood losses that will serve as the sum insured in the form of insurance products. Analysis mixture consisting of identification areas, conditions, and alternative insurance models used to establish the right flood insurance for Baleendah. Results show the estimation of flood losses and flood insurance appropriate to the condition of Baleendah.

The purpose of this paper is to examine the volatility of Islamic stocks related to the causality of the composite stock price index (CSPI). The aim is to investigate the causality of several levels of stock returns with the movement of the CSPI, and determine its volatility as a measure of risk. To determine the causality relationship is done by using the granger causality test method, with Vector Autoregressive (VAR) modeling. Whereas to determine the volatility is done using the Generalized Autoregressive Conditional Heteroscedastisiy (GARCH) model approach. The results of the causality test show that there is a direct relationship that affects and is influenced by the CSPI, and the relationship that affects each other between the company's stock market and the movement of the CSPI. While the volatility follows the GARCH model (1, 1). Based on the results of this study are expected to be used as consideration in making investment decisions in the analyzed stocks.

Dalam artikel ini, dipelajari tentang aljabar Lie affine berdimensi 6 yang sekaligus merupakan aljabar Lie Frobenius. Terdapat fungsional linear atau 1-form yang mengakibatkan aljabar Lie affine merupakan aljabar Lie Frobenius. Tujuan penelitian ini adalah untuk membuktikan bahwa fungsional linear tertentu yang dipilih dapat dihitung secara eksplisit dan berkorespondensi dengan struktur 2-form. Diberikan juga pemetaan antara aljabar Lie affine dengan ruang dualnya yang juga didefinisikan berkaitan dengan 2-form-nya. Hasil yang diperoleh menunjukkan eksistensi fungsional linear tersebut mengakibatkan adanya skew-symmetric nondegenerate closed 2-form yang merupakan turunan pertama dari fungsional linearnya.  Selanjutnya, dihitung juga elemen utama dari aljabar Lie affine berdimensi enam. Kata kunci : Aljabar Lie Affine, Aljabar Lie Frobenius, Fungsional Linear, 2-Form, Ruang Vektor Dual.

This research aimed to estimate the length of the Citarum watershed boundary because the data are still unknown. We used the concept of fractal’s power law and its relation to the length of an object, which is still not described in other research. The method that we used in this research is the Box-Counting dimension. The data were obtained from the geographic information system. We found an equation that described the relationship between the length and fractal dimension of an object by substituting equations. Following that, we modified the algorithm of Box-Counting dimension by consideration of requiring a high-resolution image, using the Canny edge detection so that the edges look sharper and the dimension values are more accurate. A Box-Counting program was created with Python based on the modified algorithm and used to execute the Citarum watershed boundary’s image. The values of ε and N were used to calculate the fractal dimension and the length for each scale by using the value of C=1, assuming the ε as the ratio between the length of box and the length of plane. Finally, we found that the dimension of Citarum watershed boundary is approximately 1.1109 and its length is 770.49 km.

Value at Risk (VaR) has already becomes a standard measurement that must be carried out by financial institution for both internal interest and regulatory. VaR is defined as the value that portfolio will loss with a certain probability value and over a certain time horizon (usually one or ten days). In this paper we examine of VaR calculation when the volatility is not constant using generalized autoregressive conditional heteroscedastic (GARCH) model. We illustrate the method to real data from Indonesian financial market that is the stock of PT. Indosat Tbk.