Graphene as an Active Material for Supercapacitors: A Machine Learning Approach

Jamaluddin, Anif; Nursanti, Annisa Dwi; Nur'aini, Anafi; Putri, Rekyan Regasari M; Arshad, Muhammad Usama

doi:10.13057/ijap.v13i2.76678

Jurnal SINTA 1

Graphene as an Active Material for Supercapacitors: A Machine Learning Approach

INDONESIAN JOURNAL OF APPLIED PHYSICS · Vol. 13 No. 2 (2023) · hlm. 305–312

DOI: 10.13057/ijap.v13i2.76678
ISSN: 2477-6416, 2089-0133
Terbit: 2023-11-02
Penerbit: Department of Physics, Sebelas Maret University
Bahasa: eng

Abstrak

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.

Kata kunci

Jaringan kolaborasi para penulis

14 penulis · 31 tautan kepenulisan bersama

Arahkan kursor atau ketuk sebuah nama untuk menyorot rekan penulisnya. Klik dua kali untuk membuka halaman penulis.

Hasanuddin University
Afiliasi tidak diketahui

Organisasi berbeda
Organisasi sama
Afiliasi tidak diketahui
Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel

Tampilkan sebagai tabel

Rekan penulis	Organisasi	Artikel bersama
Agus Purwanto	Afiliasi tidak diketahui	2
Arif Jumari	Afiliasi tidak diketahui	2
Diky Nurkhoerudin	Afiliasi tidak diketahui	1
Daru Wahyuningsih	Afiliasi tidak diketahui	1
Anis Nazihah	Afiliasi tidak diketahui	1
Hari Maghfiroh	Afiliasi tidak diketahui	1
Muhammad Nizam	Hasanuddin University	1
Inayati Inayati	Afiliasi tidak diketahui	1
Mufti Reza Aulia Putra	Afiliasi tidak diketahui	1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://jurnal.uns.ac.id/ijap/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.

Metadata asli (oai_dc)

<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">Graphene as an Active Material for Supercapacitors: A Machine Learning Approach</dc:title>
	<dc:creator>Jamaluddin, Anif</dc:creator>
	<dc:creator>Nursanti, Annisa Dwi</dc:creator>
	<dc:creator>Nur'aini, Anafi</dc:creator>
	<dc:creator>Putri, Rekyan Regasari M</dc:creator>
	<dc:creator>Arshad, Muhammad Usama</dc:creator>
	<dc:subject xml:lang="en-US">Graphene; Machine Learning; Surface area; Supercapacitors</dc:subject>
	<dc:description xml:lang="en-US">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.</dc:description>
	<dc:publisher xml:lang="en-US">Department of Physics, Sebelas Maret University</dc:publisher>
	<dc:contributor xml:lang="en-US">Universitas Sebelas Maret</dc:contributor>
	<dc:date>2023-11-02</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jurnal.uns.ac.id/ijap/article/view/76678</dc:identifier>
	<dc:identifier>10.13057/ijap.v13i2.76678</dc:identifier>
	<dc:source xml:lang="en-US">INDONESIAN JOURNAL OF APPLIED PHYSICS; Vol 13, No 2 (2023): October; 305-312</dc:source>
	<dc:source>2477-6416</dc:source>
	<dc:source>2089-0133</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jurnal.uns.ac.id/ijap/article/view/76678/42521</dc:relation>
	<dc:relation>https://jurnal.uns.ac.id/ijap/article/downloadSuppFile/76678/13812</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 INDONESIAN JOURNAL OF APPLIED PHYSICS</dc:rights>
</oai_dc:dc>