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"Penggunaan minyak sawit sebagai bahan baku bahan bakar memiliki isu keberlanjutan. Studi keberlanjutan sebelumnya telah membahas isu lingkungan dari bahan bakar nabati berbasis kelapa sawit, tetapi belum memperhatikan aspek manusia. Secara konseptual, pendekatan keberlanjutan adalah keseimbangan antara aspek sosial, ekonomi, dan lingkungan. Penelitian ini bertujuan untuk menganalisis indikator keberlanjutan rantai pasok produksi bahan bakar nabati berbasis kelapa sawit campuran Fatty Acid Methyl Ester (FAME), Hydrotreated Vegetable Oil (HVO), dan Minyak Solar menggunakan Life Cycle Sustainability Assessment (LCSA). Emisi gas rumah kaca, ekosistem, dan kesehatan manusia diperhitungkan sebagai aspek lingkungan, kemudian biaya produksi, penghematan devisa, dan kerugian pungutan ekspor sebagai aspek ekonomi, dan penciptaan lapangan kerja dan pendapatan sebagai aspek sosial. Pembobotan ketiga aspek keberlanjutan diterapkan secara setara, kemudian dinilai berdasarkan peringkat indikator keberlanjutan. Campuran FAME, HVO, dan minyak solar diskenariokan berdasarkan standar kualitas EURO1, EURO2/3, EURO4, dan EURO5. Hasil LCSA menunjukkan EURO5 memiliki kinerja keberlanjutan tertinggi dengan skor 3,22, sedangkan EURO1 memiliki kinerja keberlanjutan terendah dengan skor 2,00. Penggunaan minyak kelapa sawit (CPO) memberikan kontribusi terhadap kinerja lingkungan dan ekonomi. Land-use change dan harga dari CPO adalah parameter yang paling signifikan mengurangi kinerja lingkungan dan ekonomi, di sisi lain juga menciptakan lapangan pekerjaan dan meningkatkan pendapatan seiring semakin tingginya campuran bahan bakar nabati. Dari hasil LCSA disarankan untuk memenuhi spesifikasi kualitas bahan bakar serta pemilihan bahan baku yang berkelanjutan.

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The use of palm oil as a raw material for fuel has sustainability issues. Previous sustainability studies have addressed the environmental issues of palm oil-based biofuels, but have not considered the human aspect. Conceptually, the sustainability approach is a balance between social, economic, and environmental aspects. This study aims to analyze supply chain sustainability indicators for the production of palm oil-based biofuels with a mixture of Fatty Acid Methyl Ester (FAME), Hydrotreated Vegetable Oil (HVO), and Diesel Oil using the Life Cycle Sustainability Assessment (LCSA). Greenhouse gas emissions, ecosystems, and human health are taken into account as environmental aspects, then production costs, foreign exchange savings, and export levy losses as economic aspects, and job creation and income as social aspects. The weighting of the three sustainability aspects is applied equally, then assessed based on the ranking of sustainability indicators. The mixture of FAME, HVO, and diesel oil is screened based on the EURO1, EURO2/3, EURO4, and EURO5 quality standards. The LCSA results show that EURO5 has the highest sustainability performance with a score of 3.22, while EURO1 has the lowest sustainability performance with a score of 2.00. The use of palm oil (CPO) contributes to environmental and economic performance. Land-use change and the price of CPO are the parameters that most significantly reduce environmental and economic performance, while also creating jobs and increasing income as the biofuel mix increases. From the results of the LCSA, it is recommended to meet the fuel quality specifications as well as the selection of sustainable raw materials."

"Masalah lingkungan telah menjadi salah satu perhatian masyarakat dunia saat ini. Penurunan kualitas, daya tampung, dan daya dukung lingkungan berangsur-angsur terjadi secara alamiah, namun disisi lain pencemaran dan perusakan lingkungan yang bersumber akibat kegiatan manusia. Salah satu aktivitas manusia yang berpotensi meningkatkan dampak lingkungan adalah produksi tahu. Tahu adalah makanan khas tradisional Indonesia yang berbahan baku kedelai dan dijadikan sebagai hidangan lauk pauk. Tujuan penelitian ini adalah mengkaji sustainabilitas industri tahu pada Usaha Kecil Menengah Tahu.Metode yang digunakan pada penelitian ini adalah metode Life Cycle Assessment dengan bantuan software Simapro 8.4 dengan unit fungsi 1 kg tahu dan dipadukan dengan metode Life Cycle Costing dan Social Life Cycle Assessment. Data yang dikumpulkan pada penelitian ini adalah data rata-rata produksi tahu selama 3 bulan, yaitu Bulan Januari - Bulan Maret 2018. Data penelitian ini meliputi proses budidaya kedelai, proses transportasi pengiriman kedelai, air, kayu bakar, dan penggunaan listrik. Batasan penelitian ini adalah dari cradle (budidaya kedelai) sampai gate (produk tahu).Hasil penelitian menunjukan bahwa industri tahu pada aspek ekonomi disetiap 1 kg tahu memiliki keuntungan 403,37 rupiah, pada aspek sosial memiliki nilai 3 dengan indikator baik, dan dampak lingkungan kondisi sekarang tanpa adanya pengolahan limbah cair memiliki potensi dampak pemanasan global dengan nilai sebesar 3,84 kg CO2-ek. Berdasarkan hasil penelitian ini perlu adanya perbaikan, maka intervensi yang dapat dilakukan adalah mengoptimalkan proses produksi.

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Environmental problems have become one of the concerns of the world community today. Decreasing quality, carrying capacity, and carrying capacity of the environment gradually occurs naturally, but on the other hand pollution and environmental damage resulting from human activities. One human activity that has the potential to increase environmental impact is tofu production. Tahu is a traditional Indonesian specialty made from soybeans and used as a side dish. The purpose of this study is to assess the sustainability of the tofu industry in Small and Medium Enterprises.The method used in this study is the Life Cycle Assessment method with the help of Simapro 8.4 software with a function unit of 1 kg to know and combined with the Life Cycle Costing method and the Social Life Cycle Assessment. The data collected in this study is the average data of tofu production for 3 months, namely January - March 2018. The data of this study include the process of soybean cultivation, transportation processes for shipping soybeans, water, fuel wood, and electricity use. The limitations of this study are from cradle (soybean cultivation) to gate (tofu products).The results showed that the industry knew on the economic aspect in every 1 kg of tofu had a profit of 403.37 rupiah, the social aspect had a value of 3 with a good indicator, and the environmental impact of the present condition without the treatment of wastewater had the potential impact of global warming with a value of 3, 84 kg CO2-eq. Based on the results of this study there needs to be improvement, then the intervention that can be done is to optimize the production process."

"Melihat besarnya potensi minyak kelapa sawit dan memahami kondisi pemanasan global yang kian meningkat akibat produksi gas rumah kaca oleh pembakaran fosil untuk produksi bahan bakar, produksi bahan bakar dari minyak kelapa sawit dapat menjadi solusi untuk mengurangi produksi gas rumah kaca. Tujuan penelitian ini adalah mendapatkan persentase campuran Fatty Acid Methyl Esters(FAME), Hydrogenated Vegetable Oil(HVO), Solar CN48 (SCN48), dan Solar CN53 (SCN53) agar mendapatkan Levelized Cost of Energy (LCOE) dan GlobalWarmingPotential(GWP) CO2eq yang minimum. Penelitian diawali dengan simulasi proses produksi FAME dan HVO menggunakan perangkat lunak Aspen Plus, dilanjutkan dengan menghitung GWP kemudian melakukan optimisasi multi-objektif untuk mendapatkan persentase campuran bahan bakar dengan spesifikasi bahan bakar solar sesuai dengan ketentuan Euro2 dan Euro4. Optimisasi dilakukan menggunakan perangkat lunak General Algebraic Modelling System (GAMS) menggunakan solver Cplex. Hasil optimisasi memperlihatkan bahwa skenario blendinguntuk Euro2 memiliki persentase campuran FAME 43,9-51,1%, HVO 2,6-40,1%, SCN48 15,3-17,6%, dan SCN53 46,3-100% dengan LCOE sebesar 0,55-0,864 USD/Liter dan GWP sebesar 599,46-3000,78 gCO2eq/Liter. Hasil optimisasi untuk skenario blendingberdasarkan spesifikasi bahan bakar Euro4 memiliki persentase campuran FAME 32,5%, HVO 28,6%, dan SCN53 38,8% dengan LCOE sebesar 0,637-0,786 USD/Liter dan GWP sebesar 902,69-2863,03 gCO2eq/Liter.

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Noticing the abundance potential of the palm oil and acknowledging the problem of green house gasses produced by fossils from burning fuels, utilizing the palm oil for fuels could decrease the emission caused by the fossils burning. The focus subject of this research is on the blending composition of Fatty Acid Methyl Esters(FAME), Hydrogenated Vegetable Oil(HVO), Diesel CN48 (DCN48), and Diesel DCN53 (DCN53) through minimizing Levelized Cost of Energy (LCOE) and GlobalWarmingPotential(GWP) CO2eq. The simulation is runned through Aspen Plus software, proceed by calculating the GWP, then the result of the simulations are optimized by using General Algebraic Modelling System (GAMS) with Cplex solver with diesel fuel specification based on the emission regulation stated in Euro2 and Euro 4. The result of the optimization shows the percentage of the blending composition of Euro2 specification consists of FAME 43,9-51,1%, HVO 2,6-40,1%, DCN48 15,3-17,6%, and DCN53 46,3-100% dengan LCOE sebesar 0,55-0,864 USD/Litre dan GWP sebesar 599,46-3000,78 gCO2eq/Litre. The result of of the blending composition of Euro4 specification consists of FAME 32,5%, HVO 28,6%, and DCN53 38,8% dengan LCOE sebesar 0,637-0,786 USD/Litre dan GWP sebesar 902,69-2863,03 gCO2eq/Litre."

"Life-cycle assessment of semiconductors presents the first and thus far only available transparent and complete life cycle assessment of semiconductor devices. A lack of reliable semiconductor LCA data has been a major challenge to evaluation of the potential environmental benefits of information technologies (IT). The analysis and results presented in this book will allow a higher degree of confidence and certainty in decisions concerning the use of IT in efforts to reduce climate change and other environmental effects. Coverage includes but is not limited to semiconductor manufacturing trends by product type and geography, unique coverage of life-cycle assessment, with a focus on uncertainty and sensitivity analysis of energy and global warming missions for CMOS logic devices, life cycle assessment of flash memory and life cycle assessment of DRAM. "

"The book contains the latest developments in the field of life cycle assessment (LCA) and its application. It contains numerous research articles from leading German research institutes working towards the further development of the methodology. The book provides important insights for professionals working in the field of sustainability assessment, for researchers interested in the current state of the research of the methodology and its application as well as for advanced university students in different science and engineering fields."

"Pengembangan kendaraan listrik tentunya perlu didukung oleh sistem charging station yang bisa menjangkau pengguna kendaraan listrik secara umum dan di samping itu juga bermanfaat dalam pemanfaatan energi terbarukan. Masalah dalam penelitian ini adalah mengkaji pemanfaatan energi terbarukan sebagai sumber energi CS. Idealnya kendaraan listrik menggunakan sumber energi terbarukan yang ramah lingkungan. Tujuan dari penelitian ini mengkaji strategi keberlanjutan dari Hybrid Charging station (HCS) dengan metode Life Cycle Costing (LCC), Life Cycle Assesment (LCA) dan analisis SWOT (Strengths, Weaknesses, Opportunity, hreat). Metode penelitian menggunakan metode gabungan. Hasil penelitian menunjukkan bahwa pada aspek ekonomi HCS tergolong efisien, kemudian pada aspek lingkungan komponen photovoltaic yang memberikan kontribusi terbesar terhadap dampak yang ditimbulkan. Stategi keberlanjutan HCS perlu didukung oleh seluruh stake holder yang berperan dalam  pengembangan kendaraan listrik dan infrastruktur pendukungnya. Kesimpulan penelitian adalah strategi pengembangan HCS yang tepat dapat mengurangi dampak lingkungan, meningkatkan efisiensi dan memudahkan pengembangan charging station yang ramah lingkungan.

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The development of electric vehicles certainly needs to be supported by a charging station system that can reach electric vehicle users in general and besides that is also beneficial in the use of renewable energy. The problem in this research is to examine the use of renewable energy as a CS energy source. Ideally electric vehicles use renewable energy sources that are environmentally friendly. The purpose of this study is to examine the sustainability strategy of the Hybrid Charging station (HCS) using the Life Cycle Costing (LCC) method, Life Cycle Assessment (LCA) and SWOT analysis (Strengths, Weaknesses, Opportunity, Threat). The research method uses a combined method. The results showed that on the economic aspect HCS was classified as efficient, then on the environmental aspect the photovoltaic component contributed the most to the impact. The HCS sustainability strategy needs to be supported by all stakeholders who play a role in the development of electric vehicles and their supporting infrastructure. The conclusion of the research is that the right HCS development strategy can reduce environmental impact, increase efficiency and facilitate the development of environmentally friendly charging stations."

"This book comprises recent developments in life cycle assessment (LCA) both with regards to the methodology and its application in various research fields, including mobility, engineering and manufacturing. Containing numerous original research articles from leading German research institutes, the book provides an insightful resource for professionals working in the field of sustainability assessment, for researchers interested in the current state of LCA research as well as for advanced university students in different scientific and engineering fields."

"Jumlah nilai konstruksi selesai di Indonesia dari Tahun 2009 hingga Tahun 2011 terus meningkat, khususnya pada konstruksi bangunan gedung yaitu sebesar 116%. Peningkatan tersebut diikuti oleh bertambahnya jumlah emisi gas rumah kaca yaitu CO2 sebesar 25%. Oleh karena itu, diperlukan adanya trobosan untuk meyakinkan pemilik sekaligus pengguna gedung untuk melakukan efisiensi energi, air, dan kenyamanan indoor dengan Konsep Green Building, khususnya pada tahap operasional dan pemeliharaan. Optimasi dilakukan dengan evaluasi kinerja bangunan green building dengan Metode LEED. Penilaian keberhasilan optimasi fungsi-fungsi pada existing green building dilakukan berdasarkan perhitungan biaya umur hidup bangunan pada tahap operasional dan pengelolaan dengan Metode Life Cycle Assessment (LCA). Nilai siklus yang menjadi hasil evaluasi pada optimasi ini yaitu nilai efisiensi siklus hidup terbesar dan siklus pengembalian pembiayaan tercepat.

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Increasing 116% of total building construction value completed in Indonesia during 2009 to 2011, that was followed by the progressive increase in the greenhouse gas emissions or CO2 amount by 25%. Therefore, that needs to convince the owners and users of buildings for energy efficiency, water conservation, and indoor comfort with the Green Building Concept, especially at the operational and maintenance phase.

Optimization is done by evaluating the performance of buildings to LEED method. Assessing the success of optimization functions in existing green building is based on operational and maintenance phase with the Life Cycle Assessment (LCA) Method. The result of optimization that is the largest efficiency of building life cycle and the fastest cost refund."

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Sampah plastik merupakan suatu permasalahan yang harus diperhatikan. Hal ini disebabkan oleh sifat yang dimilikinya yaitu sulit untuk diuraikan sehingga dapat mencemari lingkungan sekitar jika tidak segera diatasi. Oleh karena itu, diperlukan suatu sistem yang bersifat user friendly untuk membantu proses evaluasi pada produk kemasan plastik secara menyeluruh dengan menggunakan pendekatan Life Cycle Assessment (LCA) untuk mempermudah kerja pengguna serta meningkatkan kesadaran terkait dampak lingkungan yang ditimbulkan dari produk kemasan plastik. Untuk memperoleh sistem tersebut, perlu melalui beberapa tahapan dimulai dari studi literatur, pengumpulan data produk, pembuatan dataset, perumusan standar LCA, hingga pembuatan algoritma dari program pembelajaran mesin berbasis deep learning. Pembuatan dataset dilakukan menggunakan fitur random number yang terdapat pada software Microsoft excel. Sedangkan, untuk pengumpulan data produk serta perumusan standar LCA dilakukan berdasarkan database ecoinvent 3.7.1 yang disediakan oleh software openLCA. Metode deep learning digunakan untuk meningkatkan efisiensi di dalam melakukan pengolahan data. Di dalam proses pembuatan algoritma deep learning, dilakukan optimasi parameter yang terlibat seperti test size, random state, jumlah layer dan dense, learning rate, batch size, serta epochs agar dapat memperoleh akurasi yang optimum. Dari penelitian yang telah dilakukan, diperoleh hasil akhir berupa program prediksi skor LCA untuk produk kemasan botol plastik dengan menggunakan metode pembelajaran mesin berbasis deep learning dengan tingkat akurasi sebesar 92%.

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Plastic waste is a matter of concern. This is due to the nature it possesses i.e. it is difficult to decipher so it can pollute the surrounding environment if it is not addressed immediately. Therefore, it is necessary to have a user-friendly system to assist the evaluation process on plastic packaging products thoroughly by using the Life Cycle Assessment (LCA) approach to facilitate user to work as well as to raise awareness related to the environmental impact caused from plastic packaging products. To obtain such systems, it is necessary to go through several stages, start from literature studies, product data collection, dataset creation, formulation of LCA standards, until algorithm creation from deep learning-based machine learning programs. The dataset creation is performed using the random number features contained on Microsoft excel software. Whereas, for product data collection and formulation the LCA standards are performed based on the 3.7.1 ecoinvent database provided by the openLCA software. Deep learning methods are used to improve efficiency inside performing data processing. Inside the process of creating deep learning algorithms, involved parameter optimizations such as test size, random state, number of layers and denses, learning rate, batch size, as well as epochs are performed to obtain optimum accuracy. From the research already conducted, the final result was obtained in the form of an LCA score prediction program for plastic bottle packaging products using a deep learning-based machine learning method with an accuracy rate of 92%.

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