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All Journal Aceh International Journal of Science and Technology International Journal of Educational Best Practices
Nabilah, Muna
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Social Sciences Other

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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.
STUDENTS’ VOICES OF THE IMPLEMENTATION OF ONLINE LEARNING DURING THE PANDEMIC OF COVID-19 Nabilah, Muna; Daud, Afrianto; M. Syarfi
International Journal of Educational Best Practices Vol. 6 No. 1 (2022)
Publisher : Prodi Administrasi Pendidikan Program Pascasarjana Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/ijebp.6.1.108-120

Abstract

The pandemic of Covid-19 has massively switched education delivery in the world from face-to-face learning to online learning. This qualitative study aimed to investigate students’ voices of the implementation of online learning during the pandemic of Covid-19 in higher education context. There were eight students of English Study Program Universitas Riau involving in this study selected using the purposive sampling technique. Data were collected using semi-structured interviews and documentation. The participants’ voices were thematically analysed in terms of their learning participation, accessibility, material and assignment delivery of the online learning. This study found that the students view online  learning as learning experiences that bring both benefits and challenges. Students perceive online learning is a good choice to prevent the spread of coronavirus and a good time to improve their digital skills, but they were not really enthusiastic about its implementation. There are four major obstacles they faced, such as internet access, monotonous teaching method, limited interaction, and ineffective material and assignment delivery. The findings imply that online learning delivery in Indonesia still needs more improvement for better performance in the future. 
Co-Authors Afrianto Daud M. Syarfi Marwan Marwan Muhammad Yanis Muzailin Affan Suriadi Suriadi Zainal, Muzakir