Article Per Year (5 Year)
p-Index From 2021 - 2026
1.037
P-Index
This Author published in this journals
All Journal JURNAL DINAMIKA EKONOMI PEMBANGUNAN Jurnal Ilmu Lingkungan TELKOMNIKA (Telecommunication Computing Electronics and Control) Spektra: Jurnal Fisika dan Aplikasinya Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Acitya Ardana: Jurnal Keuangan Negara dan Kebijakan Publik PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Jurnal Geosains Terapan Scientific Contributions Oil and Gas Jurnal Ekonomi dan Studi Pembangunan (JESP)
Agus Riyanto
Universitas Indonesia
Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Materials Science & Nanotechnology Physics Social Sciences Other

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 13 Documents
Search

 1   2 
SPECTRAL DECOMPOSITION TECHNIQUE BASED ON STFT AND CWT FOR IDENTIFYING THE HYDROCARBON RESERVOIR Abdul Haris; Haryono Haryono; Agus Riyanto
Scientific Contributions Oil and Gas Vol 40 No 3 (2017)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/SCOG.40.3.50

Abstract

The spectral decomposition is one of the advanced interpretation techniques such as seismic inversion, amplitude versus offset analysis, and seismic attribute that helpful in direct interpretative approach in seismic exploration. This technique is a transformation algorithm, thus a signal can be transformed into its varying frequency contained in the seismic signal. There are a variety of spectral decomposition algorithms in the decomposing seismic signal from time domain into frequency domain. These algorithms include Short Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT). The STFT algorithm is a conventional and simple technique for computing a time-frequency spectrum, which is based on the application of Fourier transform. However, the STFT algorithm has a problem related to the frequency resolution. In its implementation, this algorithm is limited by predefi ned window length. In contrast, the CWT algorithm is believed to be able to overcome the limitation of window length. The CWT threats wavelet at certain window length, which is defi ned by the characteristics of the wavelet. In this study, the comparison between spectral decomposition technique based on STFT and CWT method was performed, particularly in its application to the synthetic and real data set. Each algorithm has its own advantages and disadvantages in decomposing the seismic signal. Further, this analysis can be used as a reference to select one of two algorithms for the specifi c application. The synthetic data set application shows that CWT algorithm produces better frequency resolution compared to STFT algorithm. In addition, the real data set application shows that time frequency section of the seismic line provides a spectral feature, which is useful to identify the hydrocarbon reservoir, which is associated with low-frequency shadow zone.
The Impact of Fiscal Incentives on Total Cost of Electrified Vehicle Ownership in Indonesia Riyanto Riyanto
Jurnal Ekonomi dan Studi Pembangunan Vol 17, No 2 (2025)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Indonesian government has provided fiscal incentives to develop a battery electric vehicle (BEV) market, such as luxury goods tax (PPnBM) exemptions, vehicle title transfer fee (BBNKB) reduction, and motor vehicle tax (PKB) reduction for BEV users. With several fiscal incentives, BEV prices are expected to compete with Internal Combustion Engine Vehicle (ICEVs), thus consumers will switch to buying and using BEVs. Consumers, however, do not solely consider the price of BEVs; they also consider the total cost of ownership (TCO). In that regard, this study aims to construct a TCO model and calculate the total cost of ownership of Electrified Vehicles (x-EVs) and ICEVs. This study also attempts to analyze the impact of various fiscal incentives on the TCO of BEV. The result of this study shows that (1) without any fiscal incentives, the amount of x-EV’s TCO (Total Cost of Ownership) is comparably higher than that of ICEV; (2) PHEV’s and HEV’s TCOs are lower than the TCO of ICEV with the provision of PPnBM-free incentives and PPnBM reduction respectively; and (3) three fiscal incentives (PPnBM exemption and BBNKB and PKB discount) are urgently required to lower the TCO of BEV and penetrate the Indonesian market.
Subsurface Natural Fracture Modelling and Prediction on Igneous Rocks of "U" Geothermal Field M. Farel Bagaskara; Felix M. H. Sihombing; Agus Riyanto
Jurnal Geosains Terapan Vol 6 No 1 (2023): Jurnal Geosains Terapan
Publisher : Lembaga Ilmu Pengetahuan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

United States of America has a promising geothermal energy potential, especially in Roosevelt Hot Springs area in Utah. Geothermal system needs fractures as a considerable aspect in geothermal system evaluation. Fracture formed by the geological condition in the area, so it can affect the characteristic of the fractures. This research aims to analyze the structural geology condition, fracture characteristic, fracture prediction accuracy, and the comparison of the fracture prediction result with the fracture model. To achieve it, there are some data processing steps, such as seismic data interpretation, building seismic attributes, building implicit fracture model, and predicting fracture occurrence using Support Vector Machine (SVM) method which is a machine learning method. The research shows the structural geology condition in the study area consists of east – west trending normal faults and north – south trending reverse faults. The fracture in the study area has a dominant trend of north – south with the intensity ranging from 0 to 3. High fracture intensity zone can be found around faults and curvatures. The fracture prediction using SVM method produces an accuracy value of 73%. Overall, the fracture prediction result is good enough, although there are some zones which have a poor result when it compared to the implicit fracture model.
Co-Authors Abdul Haris Adang Sukmatiawa Ade Rama Tanjung Putra Ambar Rachmanto Ellita Rahardyan Maharani Hapsari Setyowardhani Haryono Haryono Ika S. Oktavianti M. Farel Bagaskara Muhammad Hafiz Wahfiuddin Novrizal Rano Rano Ressy Sandrina Rio I. Sebayang Sihombing, Felix Sri Mardiyati Supriyanto Susanti, Hera Tri Aji Adi Harsanto ulfathul arzia