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"Permasalahan utama pada pengembangan teknologi renewable energy diIndonesia terletak pada nilai investasi awal yang cenderung tinggi dibandingkanteknologi fosil. Penelitian ini bertujuan untuk membuat suatu business modelcanvas penerapan teknologi renewable energy dengan skema blockchain equitycrowdfunding yang diharapkan mampu diterapkan di Indonesia. Penelitian inibersifat kualitatif dengan menggunakan data primer berupa wawancara langsungdengan responden, melakukan pengamatan langsung pada aktifitas bisnis yangterjadi, dan mencari data sekunder dari berbagai sumber untuk memperkuat datadari responden. Jumlah responden yang peneliti gunakan sebanyak 10 orang yangdikumpulkan dari berbagai pihak ahli di setiap bidang pada ekosistem bisnisblockchain dan renewable energy. Analisis yang digunakan adalah memasukkandata dari berbagai sumber tersebut kedalam 9 blok Business Model Canvas (BMC)yang selanjutnya pada setiap blok dilakukan analisis Strenght, Weakness,Opportnity, dan Threat. Dari hasil penelitian tersebut harapannya menjadi masukanyang dapat digunakan untuk pengembangan strategi bisnis bagi perusahaan yangingin menerapkan skema blockchain equity crowdfunding pada bisnis renewableenergy, serta menjadi bahan pertimbangan investor maupun user agar beranimengambil keputusan dalam berinvestasi pada ekosistem bisnis renewable energy

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The main problem in the development of renewable energy technology in

Indonesia lies in the initial investment value that tends to be high compared to fossiltechnology. This study aims to create a business model canvas for the application of renewable energy technology with the blockchain equity crowdfunding scheme that is expecting could be implemented in Indonesia. This research is qualitative in nature by using primary data in the form of direct interviews with respondents, making direct observations on business activities that occur, and looking for secondary data from various sources to strengthen data from respondents. The number of respondents that the researchers used was ten people collected from several experts in each field in the blockchain business ecosystem and renewableenergy. The analysis used is to enter data from various sources into nine blocks ofBusiness Model Canvas (BMC), which is performing on each block analysis of Strength, Weakness, Opportunity, and Threat. From the results of this research, it is hoping that it will be an input that can be used for developing business strategies for companies that want to implement the blockchain equity crowdfunding scheme in the renewable energy business, as well as being taken into consideration by investors and users to have the courage to make decisions in investing in the renewable energy business ecosystem "

"This book provides a relatively whole view of data-driven decision-making methods for energy service innovation and energy system optimization. Through personalized energy services provision and energy efficiency improvement, the book can contribute to the green transformation of energy system and the sustainable development of the society. The book gives a new way to achieve smart energy management, based on various data mining and machine learning methods, including fuzzy clustering, shape-based clustering, ensemble clustering, deep learning, and reinforcement learning. The applications of these data-driven methods in improving energy efficiency and supporting energy service innovation are presented. Moreover, this book also investigates the role of blockchain in supporting peer-to-peer (P2P) electricity trading innovation, thus supporting smart energy management. The general scope of this book mainly includes load clustering, load forecasting, price-based demand response, incentive-based demand response, and energy blockchain-based electricity trading. The intended readership of the book includes researchers and engineers in related areas, graduate and undergraduate students in university, and some other general interested audience. The important features of the book are: (1) it introduces various data-driven methods for achieving different smart energy management tasks; (2) it investigates the role of data-driven methods in supporting various energy service innovation; and (3) it explores energy blockchain in P2P electricity trading, and thus supporting smart energy management."