Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa JURNAL KELUARGA SEHAT SEJAHTERA
Handre Gabriel Pinem
Unknown Affiliation
Astronomy Health Professions Mathematics Nursing Public Health Other

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

Found 2 Documents
Search

 1 
Analisis Kemampuan Mahasiswa Matematika FMIPA Unimed dalam Menyelesaikan Pertidaksamaan Nilai Mutlak dengan Berbantuan Python Ameliya Ameliya; Dina Olivia Nainggolan; Handre Gabriel Pinem; Retno Ayu Zalianti
Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa Vol. 2 No. 5 (2024): Oktober: Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bilangan.v2i5.250

Abstract

This research aims to analyze the ability of Unimed FMIPA Mathematics students in solving absolute value inequalities with the help of the Python program. The problem faced is that students often have difficulty solving inequality problems manually. The purpose of this research is to see the effectiveness of using Python in helping to solve absolute value inequalities and how it affects understanding of mathematical concepts. The method used was qualitative research with a sample of 20 fifth semester students of the Mathematics Study Program, FMIPA, Medan State University. Students are given absolute value inequality problems to solve manually and with the help of Python. Data was collected through online tests and questionnaires using Google Form. The research results show that the majority of students feel that using Python is very helpful in solving absolute value inequalities. As many as 95% of students consider Python to be effective in making it easier to solve mathematical problems and increasing understanding of the concept of absolute value.
MODEL GEOMETRIC BROWNIAN MOTION TERMODIFIKASI KALMAN FILTER UNTUK PREDIKSI SAHAM KONSUMEN DAN IMPLIKASINYA TERHADAP STRATEGI INVESTASI KELUARGA DI INDONESIA Handre Gabriel Pinem; Tobing, Rizky Saputra; Dani, Danu Rama; Lubis, Raja Harly Anugrah; Lubis, Rhamanda Ardiyansyah; Manullang, Sudianto; Nasution, Alvi Sahrin
JURNAL KELUARGA SEHAT SEJAHTERA Vol 23 No 1 (2025): JURNAL KELUARGA SEHAT SEJAHTERA
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jkss.v23i1.58614

Abstract

Stock investment is increasingly in demand by investors because of its high profit potential, but predicting stock price movements is still difficult due to its volatile nature. The Geometric Brownian Motion Model (GBM) is commonly used for this purpose, as it captures the stochastic dynamics of stock prices, assuming a normal log-return distribution and constant volatility. However, prediction accuracy decreases over time due to the dynamic nature of the stock market. To improve prediction accuracy, the Kalman Filter is used to iteratively adjust parameters in the GBM model, resulting in a more flexible and accurate forecasting approach. Research by Maulidya et al. revealed that the combination of GBM and Kalman Filter produced a low Mean Absolute Percentage Error (MAPE) of 0.0674%, indicating high prediction accuracy. This study aims to develop a stock price prediction model for PT Unilever Indonesia Tbk (UNVR) using GBM modified with the Kalman Filter, resulting in a model that is more representative and adaptive to market changes. The methodology includes data collection, return calculation, parameter estimation, and model construction, with the results showing a MAPE of 6.8%, outperforming the traditional GBM model. The study concludes that the modified GBM-KF model is effective for short-term prediction, highlighting its ability to adapt to market fluctuations despite challenges posed by non-linearity and extreme market conditions.
Co-Authors Ameliya Ameliya Dani, Danu Rama Dina Olivia Nainggolan Lubis, Raja Harly Anugrah Lubis, Rhamanda Ardiyansyah Manullang, Sudianto Nasution, Alvi Sahrin Retno Ayu Zalianti Tobing, Rizky Saputra