Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Jurnal Teknik Industri Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Spektra: Jurnal Fisika dan Aplikasinya Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Indonesian Journal of Contemporary Multidisciplinary Research Metris: Jurnal Sains dan Teknologi
Budhi Handoko
Departemen Matematika, Fakultas MIPA, Universitas Padjadjaran
Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
Modelling Primary Energy by Long Memory Time Series Darmawan, Gumgum; Budhi Handoko
Indonesian Journal of Contemporary Multidisciplinary Research Vol. 2 No. 6 (2023): November 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/modern.v2i6.6970

Abstract

This research employs long memory modeling techniques to analyze and forecast global energy data spanning from 1965 to 2022. Focusing on the ARFIMA (Autoregressive Fractionally Integrated Moving Average) model, the study demonstrates its efficacy in predicting energy consumption trends. The evaluation of forecasting results for the subsequent four years reveals a remarkable Mean Absolute Percentage Error (MAPE) below 5%. This outcome underscores the effectiveness of incorporating long memory components in energy modeling, offering a robust approach for accurate and reliable predictions. The findings contribute to the advancement of energy forecasting methodologies, providing valuable insights for policymakers, energy analysts, and researchers in the pursuit of sustainable and informed energy planning
Co-Authors Anindya Apriliyanti Pravitasari Gumgum Darmawan Nadiyah Nisrina Rahmah, Nabila Dhia Alifa Sri Winarni Yeny Krista Franty Yudhie Andriyana Zulhanif Zulhanif