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All Journal Jurnal Fourier International Journal of Computing Science and Applied Mathematics Jurnal Riset Akuntansi Politala
Zani Anjani Rafsanjani HSM
Universitas Ahmad Dahlan
Computer Science & IT Economics, Econometrics & Finance Education Mathematics

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A Mathematical Model of Microplastic Spreading into Fish Digestive Based On Abiotic Factor Zani Anjani Rafsanjani HSM; Nurul Suwartiningsih; Ichsan I Luqmana
Jurnal Fourier Vol. 10 No. 2 (2021)
Publisher : Program Studi Matematika Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In this research, we observe the fish from seven different river location on Yogyakarta by evaluating its digestive weight. We investigate the microplastics spreading on fish digestive based on the abiotic factor such as river temperature, acidity, and river flow microplastics granules to be carried into the digestive tract of the fish. The rate of microplastics in the fish body can be describe mathematically using differential equation. We build a model based on the diagram flow of the relationship between each variables. Thus we have a differential system as the model. In the next step we analyze the model analytically. To show the accurancy of the model, we make a simulation using data simulation to the system and we compare it with the computing results using observation data. At the end of our research, we give a justification for the most influential abiotic factor for microplastic sreading.
The Dynamics of Stock Price Change Motion Effected by Covid-19 Pandemic and the Stock Price Prediction Using Multi-layered Neural Network Zani Anjani Rafsanjani; Devi Nurtiyasari; Angga Syahputra
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 7, No 1 (2021)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.v7i1.7023

Abstract

In this paper, we work on the analysis of dynamical change on stock price during Covid-19 pandemic using nonlinear deterministic motion equation. The model is given by the second-order differential equation with constant coefficient over time with some consideration under stock market structure. This coefficient shows the rate of change of stock price throughout Covid-19. Thus, the Least Square estimator is derived to determine the constant factor. Further, we conduct the Multi layered Neural Network algorithm to predict the future stock price. To provide accurate forecasting results, the algorithm used in this paper has to be able to recognize stock price data pattern which has dynamic characteristics. Multi-layered Neural Network solve the data with dynamic characteristics by using more than one hidden layer. The input layers of this network are not directly connected to the output layers of the network. Therefore, this algorithm is expected to provide accurate forecasting results. We use the Jakarta Composite Stock Price Index (IHSG) and Waskita Karya Company stock price's data for the subject of observation.
ANALISA LAJU PERUBAHAN HARGA SAHAM LQ45 MENGGUNAKAN PERSAMAAN DIFERENSIAL Zani Anjani Rafsanjani HSM
Jurnal Riset Akuntansi Politala Vol 3 No 2 (2020): Jurnal Riset Akuntansi Politala
Publisher : Pusat Penelitian dan Pengabdian bagi Masyarakat Politeknik Negeri Tanah Laut

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.774 KB) | DOI: 10.34128/jra.v3i2.68

Abstract

The stock price movement is a very interesting discussion today. Dynamic price changes every time requires deep analysis to determine trends and stock price predictions in the future. There have been many methods used to analyze and predict stock prices. This paper will analyze the acceleration of stock price changes using a mathematical approach, known as a second-order differential equation. The benefit of this research is to obtain a coefficient of change in stock prices that can be used to predict stock prices in the future. Stock prices that will be observed are stocks including the LQ45 category. Furthermore, program analysis is carried out using Matlab software. At the end of the study, the coefficient of price change for LQ45 stocks was generated through provided historical data.
Co-Authors Devi Nurtiyasari Ichsan I Luqmana Suwartiningsih, Nurul Syahputra, Angga