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This study explores the application of green hydrogen technology for industrial decarbonization, focusing on its techno-economic and environmental feasibility. A quantitative approach was used, incorporating system modeling of a solar-based hydrogen production system combined with electrolyzers. The techno-economic assessment involved calculating the Levelized Cost of Hydrogen (LCOH), estimating capital and operational expenditures (CAPEX and OPEX), and evaluating the system's energy efficiency and hydrogen output. The environmental impact was analyzed using Life Cycle Assessment (LCA), comparing the carbon footprint of green hydrogen with fossil-based hydrogen. The results reveal that green hydrogen can reduce carbon emissions by up to 60% compared to fossil hydrogen, primarily due to the use of renewable energy for production. Additionally, the study found significant improvements in energy efficiency as electrolyzer performance and solar capacity increased. The LCOH is expected to decrease steadily as solar panel and electrolyzer prices continue to fall, enhancing the competitiveness of green hydrogen in the energy market. The findings also highlight the potential for heavy industries, such as cement and steel production, to transition from fossil fuels to green hydrogen, contributing to a cleaner industrial energy mix. This transition presents both environmental and economic benefits, with long-term savings from reduced fossil fuel dependency and lower production costs.

Energy efficiency has become a cornerstone in industrial optimization, reducing operational costs and contributing to sustainability. This paper reviews key innovative approaches in mechanical systems used to enhance energy efficiency within industrial applications. It covers advances in system design, smart technologies, automation, and predictive maintenance. By understanding these techniques, industries can make strides toward greener production processes, lower energy costs, and reduced environmental impact.

Applying ergonomic principles in work tool design for manufacturing industries is a crucial factor in improving productivity while maintaining worker health. This research aims to analyze the effectiveness of adaptive work tool design models based on cognitive and physiological ergonomic principles, identify interaction patterns between workstation design and operational performance, and develop a conceptual framework for integrating ergonomic principles into production cycles. The research method adopts a cognitive-physiological approach with qualitative analysis of human-machine interactions, biomechanical simulations using digital human modeling, and muscle load measurements through electromyography. Implementation was conducted using a participatory ergonomics approach and IMU sensor-based real-time monitoring systems. Results show that using materials with controlled deformation capabilities (15-20%) in work tools reduces muscle work by up to 27%, while adaptive automation system integration improves assembly accuracy by 18%. Workstations with ergonomic adjustments increase assembly speed by an average of 12%, and low-cost ergonomic interventions effectively improve productivity by 11-15% in resource-limited environments. Longitudinal analysis reveals that evidence-based ergonomic investments yield a 230% ROI through increased productivity, reduced injury compensation costs, and decreased employee turnover. IMU-based posture monitoring systems integrated with adaptive feedback loops reduced musculoskeletal disorder incidents by up to 41%. In conclusion, ergonomic optimization based on cognitive-physiological principles creates synergy between production efficiency and worker well-being, making it an essential component in achieving sustainable productivity.

Industrial development management must be implemented optimally by business actors, it is an absolute requirement for companies to be able to develop rapidly. The strategies implemented are certainly needed by business actors, starting from utilizing market digitalization, building distribution channels, to providing services that make it easier and satisfy consumers. This research was carried out at a home industry (UMKM) for Bintang Mas Mushroom Chips in Kauman Srengat, Blitar Regency. This research is to find internal and external factors and determine alternative strategies for developing MSMEs in the Bintang Mas mushroom chips industry. The method in this research is a descriptive analysis method. With interviews, documentation and observations at the research location. As a result of the research, several internal factors were found that encouraged the development of the Kauman gold star mushroom chips industry, Srengat District, Blitar Regency. The company has employees who are competent in their fields, utilize digital marketing, fast distribution, and a friendly and good customer service model. Furthermore, external factors include increasing company income, increasing the efficiency and effectiveness of business operations, and adopting various strategies implemented by competitors. Alternative strategies used by the company, namely increasing production capacity and quantity in a continuous improvement framework to meet market demand, expanding cooperative relations between companies and farmers, companies and customers, signifying various promotions, discount strategies for chips mushrooms on certain days, product packaging quality innovation that is more creative and attractive

The MSME group "Manuggal Karya" located in Ngambarsari Village, Karang Tengah District, Wonogiri, Central Java is a business group that operates in the field of refining clove leaf essential oil. can be monitored properly so that overflowing essential oils often spill from the reservoir and improper handling can actually cause the essential oils to become dirty. The use of an automation system that can keep essential oils sterile and can stop the flow of oil to the reservoir if the reservoir is full. The result that the author hopes is that by making this tool, the MSME Group "Manunggal Karya" can increase production efficiency to produce quality clove leaf essential oil.    

This study explores the integration of hybrid AI control models, combining reinforcement learning (RL) and robust adaptive control, to improve the adaptability, performance, and stability of autonomous manufacturing systems. Traditional control systems, while effective under stable conditions, often struggle to cope with disturbances and varying production demands. Hybrid AI models, which integrate classical control methods such as Proportional Integral Derivative (PID) with machine learning techniques like RL, deep Q-networks (DQN), and deep deterministic policy gradient (DDPG), enhance decision-making capabilities in dynamic production environments. The study develops a hybrid RL robust control framework and tests it in both simulation and real-world scenarios. Performance metrics, including production efficiency, system stability, and adaptability, are assessed under various disturbance conditions, such as machine failures and fluctuating demands. The hybrid model significantly outperforms traditional PID control in terms of efficiency and stability, demonstrating faster convergence and better adaptability in dynamic environments. Statistical analysis confirms the superiority of the hybrid system over standalone RL models and traditional PID control. This model’s scalability and adaptability make it a promising solution for Industry 4.0 applications, addressing key challenges in real-world manufacturing systems by ensuring computational efficiency and the ability to manage large-scale data. The findings contribute to the development of more robust and efficient control strategies for autonomous manufacturing systems in uncertain environments.

Waste management poses an inevitable challenge in human life and is often poorly handled. One type of waste causing significant issues is solid organic waste from households, which can lead to unpleasant odors and soil and water pollution due to its high organic content. However, the potential of organic waste to be converted into biogas, as an alternative energy source, can be harnessed through anaerobic processes. In this experiment, the researchers aimed to observe the effectiveness of adding additives to organic waste with varying doses. The organic content in the substrate for anaerobic microbes was represented by VS (volatile solid), with the inoculum sourced from cow dung. The experiment results indicate that adding NPK fertilizer additives with different doses increases biogas production. This suggests that the use of NPK additive can enhance the efficiency of anaerobic processes in generating biogas from organic waste.

The application of appropriate technology has an important role in increasing the production capacity and product quality of MSMEs. This service aims to increase the production capacity of Safnur MSMEs in Lengkong Village, Rakit District, Banjarnegara Regency through the implementation of a spinner tool. The results of the service showed that the use of the spinner tool succeeded in increasing production capacity from 10 kg to 15 kg per day, as well as reducing drying time by up to 66%. In addition, the quality of banana chips products also increases significantly with lower oil content, resulting in products that are crisper and last longer. The training and assistance provided to Safnur MSME workers ensures optimal use of spinner tools, increasing production efficiency and consistency. The implications of the results of this service are not only increasing income and business sustainability of Safnur MSMEs but also opening up new job opportunities for the surrounding community. This success can be used as a model for the development of other MSMEs in the area. Recommendations are given for the continued use of spinner tools and the development of MSMEs through appropriate technology support, ongoing training, and collaboration with the government and related institutions.

This study aims to empower farmer groups in applying appropriate technology to rice farming productivity in Sukajadi Village, Sadananya District, Ciamis Regency. The research methods used include field surveys and analysis of productivity data from farmers who apply this technology compared to those who do not. Primary data was collected through structured interviews with farmers and direct observation in the field during the research period. Data analysis was carried out by comparing rice production results, efficiency of using agricultural inputs, and farmer income before and after adopting appropriate technology. The research results show that the adoption of appropriate technology significantly increases rice productivity in terms of the number of harvests per hectare and reduces the costs of certain inputs such as fertilizers and pesticides. In addition, farmers who apply this technology also report better income increases compared to conventional methods. These findings support the importance of implementing appropriate technology in improving food security and the economy of farmers in rural areas such as Sukajadi Village. This research contributes to expanding understanding of the practical benefits of appropriate technology in the context of rice farming in Indonesia.

The service was done in Ngaglik and Pancuran villages, Gondangrejo, Karanganyar, Central Java. These areas have the potential to produce mats with semi traditional method. Most of the villagers are the mats’ weavers and worker of the weavers. The village has a potential in developing the craft of mats. The main problem from the craftsmen are the management, the production process is less than optimal, no efficiency in production process and the management of the marketing. In this service, many activities are held such as training in management and creativity, displaying of the technology’s application, and marketing technique for the product. The result of this service with Ibm are the optimal production process and the handling of the marketing.Keywords: Mats, productivity, craftsmen, production

The use of quality cost reports in quality improvement programs is a strategy that aims to increase the efficiency of a company's production costs. Quality cost reports include the identification, measurement, and analysis of costs associated with product or service quality deviations. In this context, research discusses the importance of integrating quality cost reports in an effort to improve product or service quality while minimizing production costs. This study demonstrates how the use of quality cost reports can provide valuable insights for companies in identifying the most effective and efficient resources for quality improvement. Quality cost analysis can help management make the right decisions regarding resource allocation, production process development, and implementation of continuous improvement.

This research investigates the impact of internal conflict and communication quality on the performance efficiency of production team members in the EDT Division. With a qualitative and quantitative analysis approach, this study explores how internal conflict and good or bad communication affect the productivity and performance of production teams. The findings from this research provide valuable insights for management to understand production team dynamics and formulate effective strategies to increase efficiency.    

Quality cost analysis is an important approach in measuring the efficiency and effectiveness of a company's production process. Focusing on the number of product defects is a critical element in quality evaluation, as defects can impact customer satisfaction, company reputation, and overall business sustainability. This research explores the significance of quality cost analysis as a tool for measuring the number of product defects in the manufacturing industry. Through data collection and statistical analysis, this research aims to provide in-depth insight into the economic impact of product defects and how quality cost analysis can help companies identify, measure and manage these aspects more efficiently. It is hoped that the results of this research will provide practical guidance for companies in improving the quality of their products while optimizing costs associated with nonconformities.

The rapid development of technology will obtain excellent effectiveness and efficiency from sources of electrical energy owned by a company or agency. With the progress of the industrial world today, the development of digital technology which ends in computer systems indirectly makes control technology involved as part of this progress. The availability of a power source is a very important aspect in the midst of technological developments. However, because the system is very complex, starting from the power plant to distribution to consumers, there is a high possibility of disturbances that can cause the flow of electrical energy to consumers to be cut off. There are certain places including factories, offices, banks, campuses, hospitals, airports and other places that could potentially endanger one's safety or drastically disrupt the course of the economic cycle. The flow of electrical energy must not be interrupted for a very long time because it can hamper the production process. and others, so that additional supply is needed to anticipate when the electricity is cut off from the National Power Plant source.

The accounting information system is an integral part of the overall system formed and implemented by a company. The long-term success of a company heavily depends on the effectiveness of the accounting information system used. PT Mitra Perkasa Harapan, a company engaged in the production and sale of foam mattresses, requires an appropriate accounting information system to support its operations. This research aims to evaluate the implementation of the Accounting Information System at PT Mitra Perkasa and find the best ways to improve it according to the correct procedures. This research utilizes the analytical descriptive method, which involves collecting relevant data and information to be analyzed to reach accurate conclusions. Data collection is conducted through interviews and observations. The research findings indicate that the implementation of the Accounting Information System at PT Mitra Perkasa is still not optimal, as evidenced by the dual roles played by several functions within the organization. To achieve efficiency and compliance with the correct procedures, adjustments are needed in managing the accounting information system. Improvement measures should be based on careful analysis and interdepartmental coordination to ensure that the implemented system aligns with the company's needs and established standards. Consequently, the company can enhance its operational performance and better achieve its long-term goals.

Competition in the industrial world after the impact of Covid-19 has become fierce competition. Many companies choose to increase effectiveness and efficiency by implementing digitalization in production and sales activities. PT. Megarhizo Ega Persada is a company that is developing, a company whose main production is liquid organic fertilizer under the brand "Megarhizo". Production activities still use manual bookkeeping processes. So it takes a long time for distribution from the warehouse to the production location. Miscalculations often occur in warehouses resulting in inappropriate production targets, due to insufficient or expired materials due to being in the warehouse for too long. This problem often occurs because the recording process is not thorough and results in stock buildup or stock shortages in the warehouse. So we need a system that can easily and quickly manage data so that these things don't happen again. Digitalization of the sales process is a solution to this problem, fertilizer products are products that are different from other production, because fertilizer is a product that is monitored so the price of fertilizer should not burden the public. By digitizing sales, companies can directly monitor stock and products sold from each distribution location to the resellers. So the number of products sold and prices can still be monitored, besides that the company can also find out the effectiveness of fertilizer production.

In the agricultural sector, the automatic identification of chili pepper varieties is crucial for improving production efficiency and quality. This study developed a chili pepper variety detection system based on characteristics using the Principal Component Analysis (PCA) method. The PCA method was used to reduce the dimensionality of chili pepper image data, thereby facilitating the classification process while retaining the key features necessary for chili pepper variety identification. The recognition system for chili pepper identification involves inputting chili pepper image data into a computer. The computer then interprets and identifies the chili pepper variety, and the test data utilizes a dataset of chili pepper images from various varieties. The research results indicate that the proposed system achieves a high level of accuracy in detecting and classifying chili pepper varieties. Consequently, this system can assist farmers and agricultural industry stakeholders in the chili pepper sorting and selection process, thereby improving operational efficiency and the quality of the harvest.

This paper presents an optimization approach for a hybrid photovoltaic (PV)-wind-battery energy system tailored for remote areas in Indonesia. Due to the archipelagic nature of the country, many remote areas lack access to the national power grid, making renewable energy solutions crucial. This study utilizes a genetic algorithm to optimize system configurations, balancing energy production, storage requirements, and cost efficiency. Results indicate that the proposed hybrid system can meet local demand with high reliability and at lower costs compared to diesel generators. The study also addresses environmental and social impacts, proposing sustainable energy strategies for Indonesia's underserved regions.

This study explores an artificial intelligence (AI)-based predictive maintenance system for industrial machinery in Indonesian manufacturing. By utilizing machine learning algorithms, the system can analyze real-time machine data to predict equipment failures and recommend timely maintenance actions. The implementation of predictive maintenance has shown to reduce machine downtime by 20% and improve operational efficiency in manufacturing plants in Jakarta and Surabaya. This paper discusses the technical design of the predictive maintenance system, its economic impact on production costs, and implications for Indonesia's industrial sector.

This sharing session activity aims to find solutions to the problem of increasing business productivity among MSME players. This activity is the result of a collaboration between STIEM Bongaya Makassar and the Bali chapter of the TDA foundation which was held at the Wistara cafe, Badung Regency, Bali with the theme of MSME revival activities. The activity method is carried out through sharing sessions by forming a group discussion forum (FGD) where the presenters and participants provide input to each other and formulate appropriate strategies to increase business productivity. One of the conclusions obtained is that increasing productivity among Micro, Small and Medium Enterprises (MSMEs) can be the key to business success and growth in the form of increasing production efficiency, improving product quality, improving marketing, improving skills and knowledge, increasing cooperation.