Article Per Year (5 Year)
p-Index From 2021 - 2026
1.288
P-Index
This Author published in this journals
All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) Jurnal Materi dan Pembelajaran Fisika PROSIDING : Seminar Nasional Fisika dan Pendidikan Fisika JFA (Jurnal Fisika dan Aplikasinya) INDONESIAN JOURNAL OF APPLIED PHYSICS ALCHEMY Jurnal Penelitian Kimia Kumawula: Jurnal Pengabdian Kepada Masyarakat Jurnal Fisika Indonesia Indonesian Journal of Electrical Engineering and Computer Science Automotive Experiences Jurnal Pengabdian Masyarakat Bhinneka Jurnal Pengabdian Masyarakat Bangsa Proceeding of International Conference on Biology Education, Natural Science, and Technology
Anif Jamaluddin
Program Studi Fisika Fakultas Keguruan Dan Ilmu Pendidikan, Jurusan Fisika, FMIPA, Universitas Sebelas Maret Surakarta, Jl. Ir. Sutami No. 36 A, Surakarta 57126
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : INDONESIAN JOURNAL OF APPLIED PHYSICS

 1 
Influence of Mixing Time to Crystal Structure and Dielectric Constant of Ba0,9Sr0,1TiO3 Dianisa Khoirum Sandi; Agus Supriyanto; Anif Jamaludin; Yofentina Iriani
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 5, No 02 (2015): October
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v5i02.290

Abstract

Barium Strontium Titanate (Ba1-xSrxTiO3) or BST has been synthesized using solid state reaction method. Raw materials of BST were BaCO3, SrCO3, and TiO2. Those materials were mixed, pressed, and sintered at temperature 1200oC for 2 h. Mixing time of raw materials was varied to identify its effects on crystal structures and dielectrics constant of Ba0.9Sr0.1TiO3 using X-Ray Diffraction (XRD) and LCR meter instrument, respectively. The results of XRD showed that crystals structure of Ba0.9Sr0.1TiO3 is tetragonal. Lattice parameter of Ba0.9Sr0.1TiO3 for 6 h of mixing time is a = b = 3.988 Å and c = 3.998 Å. Lattice parameter of Ba0.9Sr0.1TiO3 for 8 h of mixing time is a = b = 3.976 Å and c = 4.000 Å. Crystalline size of Ba0.9Sr0.1TiO3 was calculated using Scherrer equation. Crystalline size, crystallinity, and dielectric constant of Ba0.9Sr0.1TiO3 for 6 h of mixing time is 38 nm, 96%, and 115 at frequency 1 KHz, respectively while their value for 8 h of mixing time is 39 nm, 96%, and 196 at frequency 1 KHz, respectively. Thus it can be concluded that mixing time affects the lattice parameters of Ba0.9Sr0.1TiO3 crystal. The longer mixing time causes crystalline size, crystallinity, and dielectrics constant increase.
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 Agus Purwanto Agus Supriyanto Agus Supriyanto Anafi Nur'aini Anafi Nur'aini Anafi Nur’aini Annisa Dwi Nursanti Arif Jumari Arifa, Aulia D.P. Sasongko Danang Purwanto Dewanto Harjunowibowo Dewanto Harjunowibowo Dianisa Khoirum Sandi Dimas Rahadian Aji Muhammad, Dimas Rahadian Aji Dwi Teguh Rahardjo Dwi Teguh Rahardjo Edy Wiyono Eka Lutfi Septiani Fildhaz Khairina Nisa Fita Listiana Hendri Widiyandari Inayati Inayati Lita Rahmasari Lita Rahmasari Maghfiroh, Hari Meisya Istiqomah Muhammad Ikhsanudin Muhammad Nizam Muhammad Usama Arshad Neka Nur Aida Nugroho, Lilik Andre Nugroho, Panji Setyo Prasetyawati, Farah Yuki Pratiwi Restu Murti, Pratiwi Restu Putra, Mufti Reza Aulia R. Gernowo Ramona Safitri, Ramona Rekyan Regasari M Putri Santika, Yuriz Ananda Santosa, Fajar Julian Sri Budiawanti Subarwanti, Yunita Suharno Suharno Sukarmin, S Syamsuddin, Frendi Ihwan Ulwan, Rozin Fata W. Sulistya Wahyudi Wahyudi Wardani, Raden Roro Ilma Kusuma Widiyanto Widiyanto Yofentina Iriani Yofentina Iriani Yofentina Iriani Yofentina Iriani Yulianto Agung Rezeki