Implementasi Metode Numerik dan Simbolik dengan Python untuk Penentuan Nilai Limit Fungsi

This study analyzes the utilization of Python as a tool for calculating function limits, with an emphasis on the application of the SymPy and NumPy libraries. The flexibility of Python allows researchers to perform mathematical calculations efficiently, employing both the symbolic approach provided by SymPy and the numerical methods offered by NumPy. SymPy facilitates the management of complex mathematical expressions and produces accurate symbolic results, while NumPy provides speed and efficiency in executing numerical computations. With active community support and regular updates to the libraries, Python proves to be a robust and flexible environment for research in the field of mathematics. Findings from this study indicate that the combination of these two libraries not only enhances the accuracy of limit calculations but also accelerates the research process, making it a relevant choice in both academic and practical contexts..

Authors

Institutions

Publication Details

Journal
Pentagon Jurnal Matematika dan Ilmu Pengetahuan Alam
Published
2024-10-25
DOI
https://doi.org/10.62383/pentagon.v2i4.279
Citations
1
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.78
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Implementasi Metode Numerik dan Simbolik dengan Python untuk Penentuan Nilai Limit Fungsi

Anita Talia, Angelica Angelica, Agatha Anggraini Tumanggor, Febryanti Hasibuan et al.
1 citations
Pentagon Jurnal Matematika dan Ilmu Pengetahuan Alam
Data Mining and Machine Learning Applications
0.78
article

Implementasi Metode Numerik dan Simbolik dengan Python untuk Penentuan Nilai Limit Fungsi

Anita Talia, Angelica Angelica, Agatha Anggraini Tumanggor, Febryanti Hasibuan, Roberto Karlos Sinaga, Ocha Hosea Sigalingging
article en
1 citations

Abstract

This study analyzes the utilization of Python as a tool for calculating function limits, with an emphasis on the application of the SymPy and NumPy libraries. The flexibility of Python allows researchers to perform mathematical calculations efficiently, employing both the symbolic approach provided by SymPy and the numerical methods offered by NumPy. SymPy facilitates the management of complex mathematical expressions and produces accurate symbolic results, while NumPy provides speed and efficiency in executing numerical computations. With active community support and regular updates to the libraries, Python proves to be a robust and flexible environment for research in the field of mathematics. Findings from this study indicate that the combination of these two libraries not only enhances the accuracy of limit calculations but also accelerates the research process, making it a relevant choice in both academic and practical contexts..

Pentagon Jurnal Matematika dan Ilmu Pengetahuan AlamVol. 2(4)
State University of Medan (ID)
Quality Education
Openalex Percentile: Top 19%
Data Mining and Machine Learning Applications
0.78
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Implementasi Metode Numerik dan Simbolik dengan Python untuk Penentuan Nilai Limit Fungsi — Anita Talia, Angelica Angelica, et al. · Pentagon Jurnal Matematika dan Ilmu Pengetahuan Alam (2024) | TGRS Research Map | TGRS