Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal INDONESIAN JOURNAL OF APPLIED PHYSICS
Anafi Nur'aini
School of Energy Systems, LUT University
Astronomy Energy Materials Science & Nanotechnology Physics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Graphene as an Active Material for Supercapacitors: A Machine Learning Approach Anif Jamaluddin; Annisa Dwi Nursanti; Anafi Nur'aini; Rekyan Regasari M Putri; Muhammad Usama Arshad
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 13, No 2 (2023): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v13i2.76678

Abstract

Graphene is a promising material for supercapacitors due to its unique properties, which influence the device's supercapacitor. This study aims to investigate the key factor of graphene properties in supercapacitors (, with the goal of improving their performance. Also, we observe the machine learning models for predicting capacitance of supercapacitor including four algorithms of machine learning: Linear Regression (LR), lazy IBK, Decision Table (DT), and Random Forest (RF). Machine learning model showed that the RF model demonstrated the highest correlation value of 0.745, surpassing other models. Also, the study revealed that graphene has a high specific surface area and highly porous structure, which enhanced the high capacitance values. Finally, these machine learning models are suitable to apply in materials sciences field for understanding the materials properties in supercapacitor.
Co-Authors Anif Jamaluddin Annisa Dwi Nursanti Muhammad Usama Arshad Rekyan Regasari M Putri