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All Journal Indonesian Physical Review Aceh International Journal of Science and Technology
Zainal, Muzakir
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Physics

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Comparative Analysis of Wind Energy Potential with Nakagami and Weibull Distribution Methods for Wind Turbine Planning Suriadi, Suriadi; Nabilah, Muna; Zainal, Muzakir; Yanis, Muhammad; Marwan, Marwan; Affan, Muzailin
Aceh International Journal of Science and Technology Vol 12, No 1 (2023): April 2023
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.12.1.30736

Abstract

Wind energy is renewable energy used as an energy source for wind power plants (PLTB). The most common distribution method used to model wind speed distribution data is the Weibull distribution. The Nakagami distribution has begun to be widely used in several studies to model wind speed distribution data. The Nakagami distribution is considered an alternative to the Weibull distribution in modeling wind speed distribution data. This study aims to compare the distribution of Nakagami and Weibull in analyzing wind power potential and calculating the resulting Wind Energy Production (WEP), using wind speed distribution data from both distributions in Kuta Raja, Banda Aceh and Lhoknga, Aceh Besar. The wind speed data used is satellite data (secondary data) downloaded via windguru.cz, with the most stable wind speed being a wind speed of 3-5 m/s. The value of wind power potential at the Kuta Raja location, Banda Aceh was obtained at 64.16% with the Nakagami distribution and 62.73% with the Weibull distribution, and 73.60% with the Nakagami distribution and 73.28% at the Lhoknga location, Aceh Besar. The comparison of these two distributions produces a Weibull distribution that is superior to the Nakagami distribution for both locations, where the Weibull distribution has a smaller error value and produces a WEP value that is in accordance with the actual/observable data compared to the Nakagami distribution. In this study, the Nakagami distribution has results that make this distribution an alternative or comparison to the Weibull distribution in distributing wind speed data with further research.
USE OF ELECTRICAL RESISTIVITY FOR MAPPING THE LEACHATE DISTRIBUTION IN BLANG BINTANG SANITARY LANDFILL, ACEH DISTRICT Masrurah, Zakia; Muhni, Akmal; Yanis, Muhammad; Zainal, Muzakir
Indonesian Physical Review Vol. 9 No. 2 (2026)
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ipr.v9i2.549

Abstract

An increase in waste in urban areas, especially in landfills, can produce leachate that has the potential to pollute the environment. The Blang Bintang waste treatment facility, which uses a sanitary landfill system, is in a hilly area with complex geology dominated by andesite volcanic rocks. This study aims to identify and estimate the level of leachate contamination at the Blang Bintang landfill in Aceh using Electrical Resistivity Tomography (ERT).  Four ERT profiles were measured in the leachate treatment facility area, spanning 180 meters in length and up to 30 meters in depth. ERT data analysis using the Res2dinv software produced an accurate model with an RMS error of 10%-20%. The modeling results indicate the presence of conductive zones (5–150 Ohm.m) near the surface layers of profiles 1 and 2, suggesting leachate contamination. The electrical resistivity tomography (ERT) model further demonstrates leachate accumulation in the subsurface, which poses a potential risk to groundwater quality. In Profile 3, conductive zones (5–200 Ohm.m) are observed along the underground leachate pipeline. For Profile 4, conductive layers (15–250 Ohm.m) are attributed to seepage from the first leachate pond, indicating substantial contamination. This study provides landfill managers with valuable data on subsurface contamination that cannot be identified from surface observations. It also advances geophysical methods for environmental impact assessments.
Co-Authors Marwan Marwan Masrurah, Zakia Muhammad Yanis Muhni, Akmal Muzailin Affan Nabilah, Muna Suriadi Suriadi