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Fossil energy is well known as the most energy resource consumed by humans. However, the exploitation leads to damage both in the process of taking raw materials and in the use of those. Furthermore, the amount has become decreasing nowadays. Renewable energy could solve the energy crisis. One kind of renewable energy that has been successfully used by a human is by utilizing wind turbines. However, there are still many problems in its implementation and usage. One of the problems is the unstable generated electricity that is caused by instability of the wind speed. Inappropriate plans for utilizing wind turbines in such areas with varying wind speed could harm renewable energy investment. Therefore, forecasting the wind speed is necessary to anticipate the stability and embrace optimal produced energy. This study proposes the Long Short Term Memory (LSTM) algorithm to predict the generated energy by using the wind speed dataset. Thus, wind turbines can be utilized effectively and efficiently in the right area with sufficient average wind speed.
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2. Alat Pengukur Kecepatan Angin. (n.d.). Retrieved from http://www.alatuji.com/m/article/detail/682/alat-pengukur-kecepatan-angin
3. Budiartie, G. (2018, July 2). 7 Fakta Kebun Angin Pertama RI di Sidrap. Retrieved from https://www.cnbcindonesia.com/news/20180702131431-4-21421/7-fakta-kebun-angin-pertama-ri-di-sidrap
4. Djumena, E. (2018, January 16). Melihat PLTB Sidrap, Pembangkit Tenaga Angin Pertama di Indonesia. Retrieved from https://ekonomi.kompas.com/read/2018/01/16/090100826/melihat-pltb-sidrap-pembangkit-tenaga-angin-pertama-di-indonesia?page=all
5. Grinshpan, A., & Campbell, S. (2016). Maximum Efficiency of a Wind Turbine. Maximum Efficiency of a Wind Turbine, 6. Retrieved from https://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=4865&context=ujmm
6. Helmenstine, A. M. (2020, February 4). Know the Density of Air at STP. Retrieved from https://www.thoughtco.com/density-of-air-at-stp-607546
7. Ilmugeografi, R. (2016, September 14). Proses Terjadinya Angin dan Jenis-jenis Angin. Retrieved from https://ilmugeografi.com/fenomena-alam/proses-terjadinya-angin
8. 'Kincir-kincir angin raksasa' PLTB Sidrap: Mengejar ketinggalan dalam energi terbarukan. (2018, July 3). Retrieved from https://www.bbc.com/indonesia/trensosial-44679456
9. Papiewski, J. (2017, November 21). Horizontal Vs. Vertical Wind Turbines. Retrieved from https://education.seattlepi.com/horizontal-vs-vertical-wind-turbines-3500.html
10. Prijono, B., Prijono, B., Diterbitkan, Prijono, B., Prijono, B., & Prijono, B. (2018, April 12). Pengenalan Long Short Term Memory (LSTM) dan Gated Recurrent Unit (GRU) – RNN Bagian 2. Retrieved from https://indoml.com/2018/04/13/pengenalan-long-short-term-memory-lstm-dan-gated-recurrent-unit-gru-rnn-bagian-2/
11. Putra, Y. M. P. (2014, June 3). Cadangan Energi Fosil Indonesia Diperkirakan Habis 2025.