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All Journal Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter Jurnal Penelitian Pendidikan IPA (JPPIPA) Transcendent Journal of Mathematics and Applications
Taufiq Iskandar
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics Other

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Simulation of sea surface temperature (SST) and sea surface salinity (SSS) in the Bay of Bengal Syamsul Rizal; . Muhammad; Taufiq Iskandar; Ichsan Setiawan; Agus Satriadi,; . Radinal
Proceedings of The Annual International Conference, Syiah Kuala University - Life Sciences & Engineering Chapter Vol 1, No 2 (2011): Engineering
Publisher : Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1908.241 KB)

Abstract

The simulation of Bay of Bengal (included Andaman Sea) has been done. This investigation used equation of motion (Navier-Stokes equation).  The equation of motion was solved by means of Hamburg Shelf Ocean Model (HAMSOM). The analysis is done for the year of 2007. The National Centers for Environmental Prediction (NCEP) data for year of 2007 is used to force the Bay of Bengal.  The sea surface temperature (SST) and sea surface salinity (SSS) have been obtained and analyzed. The highest SST occurs in April 2007, while the lowest SST occurs in October 2007. The pattern of SST depends on the wind vector. From January untill June 2007, the SSS pattern is a west-east pattern. The SSS value is lower in the east and higher in the west. From July untill December, the higher value of SSS is generally in the middle of the Bay of Bengal. Generally, the value of SSS is higher in July and August, while in December and January the value of SSS is lower. Some results have been compared and consistent with the study of Vinayachandran dan Kurian (2008) and Vinayachandran and Yamagata (1998).
Kredibilitas Bhlmann Semiparametrik dengan Klaim Berdistribusi Poisson Maulidi, Ikhsan; Iskandar, Taufiq; Zahara, Annisa; Saputra, T Murdani
Transcendent Journal of Mathematics and Applications Vol 2, No 2 (2023)
Publisher : Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/tjoma.v2i2.34726

Abstract

One method for calculating premiums based on the policyholder's risk characteristics is to employ the theory of credibility, particularly the semiparametric Bhlmann model. The aim of this research is to estimate the parameters of the Bhlmann credibility model using a semiparametric approach for claim frequencies that follow a Poisson distribution. Additionally, this study compares the semiparametric model, the parametric model, and the nonparametric model for the Bhlmann model. The assumptions made in this study concern claim frequencies following a Poisson distribution. The research results reveal that the semiparametric Bhlmann credibility premium for a Poisson distribution is 0.117992. Furthermore, the comparison between parametric and semiparametric approaches shows that premiums estimated using the semiparametric approach are lower than those estimated using the parametric approach. The difference is approximately 0.0085% for the Negative Binomial distribution and 0.00085% for the two Poisson distributions. However, there is no significant difference in premium values between the semiparametric and nonparametric approaches.
Penerapan Model GARCH dan Value-at-Risk (VaR) dalam Analisis Stokastik Volatilitas Indeks LQ45 Andini, Nissa Rahma Putri; Radhiah; Iskandar, Taufiq; Oktavia, Rini
Jurnal Penelitian Pendidikan IPA Vol 11 No 8 (2025): August
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i8.11670

Abstract

Stock market volatility is a crucial factor in investment decision-making. This study analyzes the volatility of the LQ45 Index, one of Indonesia's major stock indices, using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and assesses risk through the Value-at-Risk (VaR) method. The data consists of daily closing prices of the LQ45 index from 2020 to 2024. A GARCH(1,1) model is used to estimate the conditional variance dynamically, and VaR is calculated at the 95% confidence level. The results show that the GARCH(1,1) model effectively captures volatility dynamics, with the highest daily VaR recorded at 3.21% during the first quarter of 2020. The novelty of this study lies in the explicit integration of the mathematical formulation of GARCH with VaR estimation in the context of the Indonesian stock market, particularly the LQ45 index, which is rarely addressed in pure mathematical finance literature. This approach contributes to the development of stochastic financial models and provides a quantitative framework for investment risk management.  
Co-Authors . Muhammad . Radinal Agus Satriadi, Andini, Nissa Rahma Putri Ichsan Setiawan Maulidi, Ikhsan Oktavia, Rini Radhiah Saputra, T Murdani Syamsul Rizal Zahara, Annisa