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All Journal Jurnal Nasional Holistic Science EDUCTUM: Journal Research Economic: Journal Economic and Business
Hani, Aulia
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Efficiency of Newton Polynomial Interpolation Method in Determining Stock Price Movements in a Certain Time Tampubolon, Bungaria; Tarigan, Febry Vista Kristen; Daulay, Nurfitri Humayro; Hani, Aulia
Holistic Science Vol. 4 No. 3 (2024): Jurnal Nasional Holistic Science
Publisher : Lembaga Riset Mutiara Akbar NOMOR AHU-0003295.AH.01.07 TAHUN 2021

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/hs.v4i3.790

Abstract

This research evaluates the efficiency of the Newton polynomial interpolation method in predicting stock price trends from historical data. The study was conducted using Microsoft stock price data according to Nasdaq for the period 4 November to 29 November 2024. This method creates an example of a polynomial based on divided disparities to describe patterns stock price convoy. The calculation results show that Newton interpolation is able to form stock price predictions with good accuracy, for example the stock price prediction in the 20 off index is $417.05, which is close to the historical data trend. The graph obtained also illustrates the mathematical interaction between the free index and stock prices visually. However, the accuracy of predictions is largely determined by the amount and quality of data used. Therefore, Newton's interpolation can be used as a a simple and efficient analytical tool, especially when applied in conjunction with other methods to deal with the complexity of the stock market.
Protection and Education of Street Children in Islam: A Study of Their Life Experiences Triana, Dinie; Nurmayani, Nurmayani; Putri, Amelia; Daulay, Nurfitri Humayro; Hani, Aulia
EDUCTUM: Journal Research Vol. 4 No. 2 (2025): Eductum: Journal Research
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/ejr.v4i2.962

Abstract

The phenomenon of street children is one of the complex social issues in Indonesia. Many factors contribute to children living on the streets, such as poverty, family instability, lack of access to education, and exploitation by certain parties. This study aims to analyze the protection and education of street children from an Islamic perspective, as well as the challenges they face in their daily lives. The research employs a qualitative method using interviews and observations of several street children. The findings indicate that these children encounter various obstacles, including social stigma, lack of family attention, and limited access to education and healthcare. From an Islamic perspective, children have the right to receive protection, affection, and proper education. Therefore, collaboration between families, communities, religious institutions, and the government is necessary to provide sustainable solutions for street children.
Apple Stock Price Prediction Using Stochastic Model: A Geometric Brownian Motion Study Tampubolon, Bungaria; Tarigan, Febry Vista Kristen; Daulay, Nurfitri Humayro; Hani, Aulia
Economic: Journal Economic and Business Vol. 4 No. 2 (2025): ECONOMIC: Journal Economic and Business
Publisher : Lembaga Riset Mutiara Akbar (LARISMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/ejeb.v4i2.1004

Abstract

The dynamic and fluctuating nature of stock prices poses a challenge in investment decision-making. This study aims to analyze and predict the stock price of Apple Inc. (AAPL) using the Geometric Brownian Motion (GBM) stochastic model. Historical stock price data for Apple was collected from Yahoo! Finance, including opening price, highest price, lowest price, closing price, and trading volume. The model utilizes mean return and volatility estimates to conduct a Monte Carlo simulation of potential future stock price movements. The simulation results indicate that within the next one year, Apple's stock price is predicted to be approximately $295.15, with possible variations reflecting market volatility. Sensitivity analysis reveals that mean return has a greater impact on stock prices than volatility, emphasizing the importance of a company's fundamentals in long-term investments. Model evaluation using Mean Absolute Percentage Error (MAPE) shows a low error rate, indicating that the predictions generated are fairly accurate. These findings provide insights for investors in understanding stock price behavior and developing more effective investment strategies.
Co-Authors Daulay, Nurfitri Humayro Maulana, Bintang NURMAYANI NURMAYANI Tampubolon, Bungaria Tarigan, Febry Vista Kristen Triana, Dinie