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INDONESIA
Indonesian Green Technology Journal
Published by Universitas Brawijaya
ISSN : 23554010     EISSN : 23381787     DOI : https://igtj.ub.ac.id/index.php/igtj/
Core Subject : Science, Education, Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Engineering Other
The Indonesian Green Technology Journal (IGTJ) is an international journal that publishes recent developments and emerging issues in both conceptual and experimental aspects of green and renewable technology. The Indonesian Green Technology Journal (IGTJ) publishes research results in the theoretical and experimental aspects of green science, engineering, technology, and medicine. Studies published in this journal include; Biomaterials, Green water management, Green energy development and management, Sustainable waste management, Green biotechnology, Green building and architecture, Clean production technology, Global warming technology, and Green building and architecture. This journal also emphasises the significance of green technology development, implementation, challenge, opportunity, and acceptance from an Indonesian perspective. IGTJ is publicly open for publication of review papers, short communication, and research papers. Since 2024, this journal has become an international journal and uses English for every paper that will be published.
Arjuna Subject : Ilmu Lingkungan (semua ketegori) - Ilmu Lingkungan (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 13 No. 2 (2024)" : 5 Documents clear
Recovery Potential Study of Waste Containing Carbohydrate Starch as an Alternative Raw Material of Bioethanol in Hospital Prasetiyo, Bagus Dadang; Sholihah, Qomariyatus
Indonesian Green Technology Journal Vol. 13 No. 2 (2024)
Publisher : Sekolah Pascasarjana, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.igtj.2024.013.02.01

Abstract

The aim of this research is to identify waste to assess the potential recovery of hospitalized rice waste as alternative raw material source of bioethanol. Values are calculated based on the alcoholic fermentation and distillation process which was measured by using Alcohol Meters and Cost Benefit Analysis (CBA) computation. The methodological steps used are starting with a study idea which includes literature study, waste flow system containing carbohydrate starch and determining the distribution of characteristics of waste containing carbohydrate starch. The results of the study ideas were then followed up with an initial evaluation of the potential through interviews and questionnaires. After the initial evaluation data has been collected, further data processing will be carried out using a structured survey of rice waste to the sources of production and the management of existing rice waste is evaluated. Thus, data on generation, characteristics and composition of rice waste were obtained through sampling. Data analysis was performed using statistical tests and laboratory tests, as well as the calculation of CBA. The average arise of hospitalized rice waste is 69.34 kg/day, and the average results of ethanol through the fermentation and distillation process of hospitalized rice waste is 80%. Using IRR and NPV  in CBA calculations at each of profits/benefits. Rice waste has the potential recovery as an alternative source of raw material for bioethanol, and has a value profits and benefits greater than value of the cost. IRR of rice waste from Hospital “X” is 21.54%
Analysis of Macroalgae-based Sustainable Biofuel Production: A Comprehensive Review Pranav, V Sai; R.V, Kavitha
Indonesian Green Technology Journal Vol. 13 No. 2 (2024)
Publisher : Sekolah Pascasarjana, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.igtj.2024.013.02.05

Abstract

This review provides an in-depth examination of macroalgae and its critical role in advancing biofuel production. It begins by tracing the developmental stages of macroalgae, from juvenile growth to full maturity, establishing the biological foundation for its utilization as a bioenergy feedstock. The unique advantages that position macroalgae as a highly promising and sustainable resource for biofuel generation is comprehensively discussed. A range of technologies and methodologies for production processes are critically evaluated, encompassing post-harvest processing, energy conversion pathways, and strategies for storage and transportation that maintain fuel integrity. Efficiency assessments of different production systems are examined to identify optimal approaches for large-scale application. The review later addresses the multifaceted challenges impeding the development of the macroalgae-based biofuel industry for sustainable progress. Furthermore, the discussion highlights the significant environmental contributions of macroalgae, emphasizing its potential roles in carbon sequestration, wastewater remediation, and as a source of organic fertilizers. These ecological benefits underscore the broader positive implications of integrating macroalgae into the renewable energy sector. Overall, this review offers a comprehensive synthesis of macroalgae-based biofuel production—from biological growth and technological processes to sustainability challenges and environmental advantages—providing valuable insights into the evolving frontier of green energy innovation
Climate Change Utilization Strategies Through the Lens of Technology: A Scientific Review Suryawijaya, Tito Wira Eka; Andono, Pulung Nurtantio; Yusianto, Rindra
Indonesian Green Technology Journal Vol. 13 No. 2 (2024)
Publisher : Sekolah Pascasarjana, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.igtj.2024.013.02.02

Abstract

This study sheds light on the untapped potential of AI in addressing the complex climate change challenges, simultaneously promoting energy efficiency and sustainable development. Issues such as carbon emissions and global climate shifts demand sophisticated solutions, and AI emerges as a versatile tool across various domains, including industry, renewable energy, and meteorological predictions, offering promising resolutions. The research findings unequivocally demonstrate AI's ability to optimize energy consumption, simulate solar radiation, predict severe weather conditions, and contribute to overall sustainability efforts. Despite existing challenges, such as substantial costs and data shortages, the prospects presented by AI for improving energy efficiency and embracing renewable energy sources are notably promising. The novelty of this research lies in its emphasis on AI's pivotal role in energy, meteorology, and grid management, underscoring the imperative collaborative synergy among governmental bodies, industrial players, and research institutions to drive sustainable AI innovations. This study encourages a holistic approach to harnessing AI's potential for mitigating climate change impacts and fostering a more sustainable future.
Algorithms Green AI: An Artificial Intelligence Algorithms Review for Hate Speech Videos Ari Setyawan, Ryan; Surjono, Herman Dwi; Wardani, Ratna
Indonesian Green Technology Journal Vol. 13 No. 2 (2024)
Publisher : Sekolah Pascasarjana, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.igtj.2024.013.02.03

Abstract

Hate speech is a form of abusive language and toxic language aimed at individuals, groups, races or ethnicities, genders and certain religions. The problem that occurs is the absence of a good filtering process on social media. For this reason, a filtering process is needed that aims to distinguish between video content that contains hate speech or not. The filtering process can use a classification model. This classification model uses an artificial intelligence algorithm. The purpose of this study is to conduct a literature review on algorithms that can be proposed for detecting hate speech videos. The algorithm used refers to the concept of green technology, with low energy resource consumption and minimizing negative environmental impacts. The literature study conducted obtained the CNN, BERT and LSTM algorithms for the hate speech video classification model. The three algorithms can be used as a reference to obtain a Green AI model by considering the low performance indicator parameters on the CPU, or using a fusion level that can reduce CPU performance. This is in accordance with the concept of green technology, reducing the use of computing processes that absorb large amounts of electrical energy.
Smart Waste Management in Indonesia: A Review of AI and IoT Application, Challenges, and Future Directions for Sustainable Solutions Nursetiawati; Fuqaha, Sameh
Indonesian Green Technology Journal Vol. 13 No. 2 (2024)
Publisher : Sekolah Pascasarjana, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.igtj.2024.013.02.04

Abstract

Waste management remains a significant challenge for Indonesia, as population growth and economic expansion continue to increase waste generation and strain existing disposal methods. Traditional approaches, such as open dumping, contribute to environmental degradation and inefficiencies in handling waste. However, the emergence of Artificial Intelligence (AI) and Internet of Things (IoT) technologies offers new opportunities to enhance waste management systems. This research explores the potential of AI and IoT in improving waste collection, sorting, recycling, and monitoring in Indonesia. By evaluating successful global implementations, it provides a framework for adapting these technologies to Indonesia’s unique challenges, with a focus on efficiency and sustainability. Key challenges, such as Accessibility and Reliability of Data , privacy concerns, infrastructure needs, and ethical considerations, are also addressed. In conclusion, while AI will offers great potential to improve waste management practices in Indonesia, it is crucial to address challenges such as data quality, privacy concerns, Financial and Infrastructure Requirements and Moral and Ethical Implications involved. With dedicated efforts and continuous research, AI's transformative capabilities can be fully utilized to promote sustainable and efficient waste management solutions in the country

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