Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Journal of Mathematical and Fundamental Sciences Communication in Biomathematical Sciences
Muhammad Syamsuddin
Department of Mathematics, Institut Teknologi Bandung, Bandung, 40132, West Java, Indonesia
Astronomy Chemistry Earth & Planetary Sciences Mathematics Physics Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Some Problems on the Making of Mathematical Modelling of a Profit-Loss Sharing Scheme Using Data Simulation Novriana Sumarti; Kuntjoro Adji Sidarto; Muhammad Syamsuddin; Vina Fitriyani Mardiyyah; Abu Rizal
Journal of Mathematical and Fundamental Sciences Vol. 47 No. 1 (2015)
Publisher : Institute for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.math.fund.sci.2015.47.1.1

Abstract

The mathematical model for a profit-loss sharing scheme is formulated in order to see how this scheme can replace the traditional practice of lending money against high interest by usurers. It is sourced from the musyarakah method in Islamic Syariah law and implemented for small-scale investments of traditional-market traders. They are the common target of usurers, so they may end up poorer than they were before. The main goal of the model is to find the appropriate portion of profit share, so the investment is profitable not only for the investor but also for the trader. There are three main problems in the process of formulating the mathematical model and finding optimized results. The first problem is providing the appropriate amount of data to be implemented in the model. The second problem is determining the objective function for the optimization of the portion of profit share. The last problem is determining the appropriate values of the parameters for certain types of traders. We found a significant result in determining the appropriate values of the parameters that explain the potential capability of the traders in handling larger amounts of capital to be invested in order to achieve our main goal.
Defining Causality in Covid-19 and Google Search Trends in Java, Indonesia Cases: A Retrospective Analysis Afrina Andriani br Sebayang; Enrico Antonius; Elisabeth Victoria Pravitama; Jonathan Irianto; Shannen Widijanto; Muhammad Syamsuddin
Communication in Biomathematical Sciences Vol. 4 No. 2 (2021)
Publisher : Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2021.4.2.1

Abstract

The Coronavirus disease 2019 (Covid-19) has led all countries around the world to the unpredicted situation. It is such a crucial to investigate novel approaches in predicting the future behaviour of the outbreak. In this paper, Google trend analysis will be employed to analyse the seek pattern of Covid-19 cases. The first method to investigate the seek information behaviour related to Covid-19 outbreak is using lag-correlation between two time series data per regional data. The second method is used to encounter the cause-effect relation between time series data. We apply statistical methods for causal inference in epidemics. Our focus is on predicting the causal-effect relationship between information-seeking patterns and Google search in the Covid-19 pandemic. We propose the using of Granger Causality method to analyse the causal relation between incidence data and Google Trend Data.
Co-Authors Abu Rizal Afrina Andriani br Sebayang Elisabeth Victoria Pravitama Enrico Antonius Jonathan Irianto Kuntjoro Adji Sidarto Novriana Sumarti Shannen Widijanto Vina Fitriyani Mardiyyah