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This study explores the integration of Artificial Intelligence (AI) with thermal optimization in Waste-to-Energy (WtE) systems to enhance both energy recovery and emission control. Introduction: The growing need for sustainable urban waste management has highlighted the importance of optimizing WtE systems. AI technologies, including machine learning and deep learning, have shown potential in improving the efficiency of WtE processes, especially in reducing emissions and enhancing energy recovery. Literature Review: Previous research indicates that AI has been successfully applied to various WtE technologies such as pyrolysis, gasification, and incineration, yet the integration of AI specifically for thermal optimization remains underexplored. Most studies focus on predictive models for emission reduction rather than real time thermal optimization. Materials and Method: The study proposes the development of an AI-driven framework that integrates real time data collection from IoT sensors, predictive modeling, and real time control algorithms. The system optimizes key parameters such as combustion temperature and fuel flow to enhance energy recovery and minimize emissions. The method includes data collection from operational WtE plants, followed by model development using machine learning algorithms. Results and Discussion: Initial simulations and pilot testing showed significant improvements in energy efficiency and emission reduction. AI-driven systems outperformed conventional WtE systems by optimizing operational parameters in real time. The study identifies gaps in AI integration for thermal optimization and suggests future research directions, including the integration of AI with smart grids and carbon credit systems for more sustainable WtE operations.

Shipping safety is everything that can be developed related to accident prevention measures when carrying out work in the shipping sector. Shipping safety and security is a state of fulfillment of transportation safety and security requirements in waters, ports and maritime environments. Fire extinguishing equipment is vital in ensuring operational safety on board and meeting the requirements set by SOLAS. Regular and regular maintenance is required to ensure that fire extinguishing equipment is always in a ready-to-use condition in the event of an emergency. Conducting  periodic drills aims to find out the extent of the readiness of fire extinguishing equipment to be used and its completeness. This study has the purpose of finding out: 1) Factors causing fire extinguishing equipment in KM. Lambelu is less than optimal 2) The impact that will occur if routine maintenance is not carried out on the fire extinguisher. The method used by the researcher this time is a qualitative descriptive method. The results of this study are as follows, The main causes of damage to light fire extinguishers in KM. Lambelu is the lack of inspection and supervision that is carried out periodically on the equipment, while other supporting factors are the lack of understanding and skills of the crew in operating light fire extinguishers, the use of light fire extinguishers that are not in accordance with the SOPs, and exposure to the marine environment that causes light fire extinguishers to corrode or rust. The impact of not carrying out routine maintenance is a decrease in preparedness in times of emergency, in addition to that it will cause financial losses, operational disruptions, and reduce public trust in the company.

Archives management plays a crucial role in ensuring the accountability of an organization, as proper management of archives can enhance transparency and operational effectiveness. Based on observations made at the Maluku Province Regional Library and Archives Office, several issues were identified within the current archiving system. One of the key problems is the lack of knowledge about proper archives management, which causes significant barriers during the archiving process. The office employs two archivists with high school and diploma (D3) education backgrounds. Although they have attended archives management training, the current system remains ineffective, which in turn affects work efficiency, particularly in the process of searching for archives. In many instances, the required archives are either difficult to locate or entirely missing. This study aims to assess the impact of archives management on work efficiency at the Maluku Province Regional Library and Archives Office. The research employs quantitative analysis with a sample size of 42 employees. Data were collected through a survey method, using a questionnaire to capture relevant information from the participants. Simple linear regression analysis conducted using SPSS 24 revealed that archives management accounts for 35% of the variance in work efficiency, while the remaining 65% is influenced by other factors. The findings suggest that effective archives management has a positive and significant impact on employee work efficiency. Based on the results, several practical implications are suggested: (1) the current archiving system should be maintained and improved for better performance, (2) training and development programs should be implemented to enhance the skills of archivists, (3) archivists should be equipped with specialized skills in archives management to improve overall efficiency, and (4) ongoing coaching and mentorship for archivists should be provided to ensure continuous improvement.

In facing the challenges of globalization and the demands for improving the quality of education, madrasas, as Islamic elementary education institutions, are required to manage themselves inde-pendently and adaptively. This study aims to describe in detail the quality improvement manage-ment strategy based on madrasa management at MI Tarbiyah Islamiyah, analyze the supporting and inhibiting factors in its implementation, and formulate relevant and applicable alternative strategies for quality enhancement. This research uses a descriptive qualitative approach with data collection techniques including in-depth interviews, field observations, and document studies. The main informants consist of the head of the madrasa, a senior teacher, and the head of the madrasa committee. The results show that MI Tarbiyah Islamiyah implements quality management through participatory planning, the implementation of programs based on local needs, continuous evalua-tion, and strategic follow-up actions. Supporting factors include visionary leadership, teacher training, and active involvement of the madrasah committee. Meanwhile, the main obstacles are limited human resources, operational funding, and the utilization of technology. This study high-lights the importance of collaborative leadership, a quality-oriented work culture, and local adapta-tion in the sustainable implementation of madrasah-based quality improvement management.

Developing research and community service (P2M) applications is crucial in enhancing efficiency and accuracy in managing related data at higher education institutions. This research aims to design a web-based application that simplifies the data management process for research, community service, and associated activities at Universitas Informatika dan Bisnis Indonesia (UNIBI). The research engaged the Rapid Application Development (RAD) methodology to actively incorporate stakeholders throughout the application development lifecycle, thereby guaranteeing alignment with their requirements. The results showed that the developed Application effectively resolved inaccurate data displays, manual data collection, and inefficient validation processes. Key features include a more accurate dashboard, an automated article validation tool integrated with Google Scholar, and streamlined submission community service activities. The activity submission process enhances operational efficiency and improves transparency and accountability in managing academic data. This research contributes to the broader adoption of digital solutions in educational administration, offering significant improvements in data accuracy and management at UNIBI.

The development of electric propulsion systems has become a major focus in efforts to provide energy-efficient and environmentally friendly air propulsion technology. One emerging innovation is the electric motor-based turbojet fan, which is expected to replace conventional fossil-fueled systems. As the need for energy efficiency increases, studies on electrical power consumption and airflow performance are crucial in supporting the development of new-generation propulsion systems. This study aims to evaluate the relationship between nozzle angle and the characteristics of electrical power consumption and airflow velocity in a double-spool turbojet fan. The method used is an experimental test with an ESP32-based control system. The duty cycle is set at 80% to maintain operational stability. Research data is obtained through measurements of electrical current, voltage, and airflow velocity. The nozzle angle variations tested include 13°, 19°, and 25°. The test results show a significant difference between nozzle angle variations on electrical power consumption and wind speed performance. The 13° nozzle angle produces the highest electrical power consumption, indicating a greater energy requirement to maintain airflow. Conversely, the optimal wind speed was found at an angle of 19°, indicating a balance between energy efficiency and aerodynamic performance. Meanwhile, an angle of 25° showed a decrease in performance in terms of both power and speed, making it less effective. In conclusion, the nozzle configuration has a direct influence on energy consumption and fluid dynamics in electric turbojet fan systems. This research provides an important contribution to the design of electric-based propulsion systems by emphasizing efficiency and performance aspects, while supporting the transition to environmentally friendly technologies.

Technological advancements and digital transformation have significantly impacted business management, including the consulting sector. PQM Consultants faces challenges in managing inquiries, which are still manually handled using Microsoft Excel. This manual process results in fragmented data, delays in accessing information, input errors, and difficulties in real-time monitoring of inquiry statuses. These issues affect operational efficiency, data transparency, and timely decision-making.   This research focuses on developing a web-based inquiry management platform through the Design Thinking methodology, aiming to improve the efficiency and effectiveness of inquiry handling at PQM Consultants. Adopting a qualitative case study approach, the study gathers insights through in-depth interviews, direct observations, and document reviews involving consultants and support team members who are directly engaged in the inquiry process. Research participants consist of consultants and support team members directly involved in inquiry management. The study uses a Design Thinking approach, which focuses on solving problems through repeated refinement and actively involving users throughout the development process. This framework supports the development of creative solutions by deeply understanding user needs, defining key challenges, and continuously refining ideas through prototyping and testing (Costich 2021). The Empathize stage focuses on understanding user needs and challenges. The Define stage formulates the core problems specifically. The Ideate stage generates creative ideas as potential solutions. The Prototype stage develops an initial design of the platform, which is then tested during the Test stage to gather feedback for further refinement. The results indicate that the web-based inquiry management platform effectively addresses various challenges in managing inquiry data, such as access delays, input errors, and data fragmentation. The platform enables consultants to monitor inquiry statuses in real-time, access data transparently, and make faster and more accurate decisions.

Global space is growing massively, and the current business phase has opened space for non-space actors to play a role. The government-driven space economy is shifting to commercial and new space in the initial phase. This research will examine the trajectory of Space in Indonesia and its position in the global space business phase. The research method uses a qualitative method. The study results show the trajectory of Indonesian Space, from its institutions to policies that support the growth of commercial space and new space phases. The dominance of the Government is still seen in space activities, which are mostly funded by public funds, with products resulting from the mastery of technology not yet entering the operational order. However, economic value can be generated by continuing commercial activities in the commercial space phase, namely the commercial use of space technology with data into value-added information and financial activities from the rental and import of space products by the Private Sector. Indonesia's position in the global space business phase is in the government-driven space economy, which involves several activities from commercial space.

This study examines the selection of the optimal camera for the photography and videography service company Assad ID using a combination of the Analytical Hierarchy Process (AHP) method and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The rapid development of the photography industry makes choosing the right camera a crucial factor in improving the quality of service. The weighting of criteria using AHP is based on the evaluation of photography and videography experts, including technical specifications, functional features, economic aspects, comfort, and supporting services. The TOPSIS method is applied to the ranking of five alternative cameras (Sony A7 III, Canon EOS R6, Nikon Z6 II, Panasonic Lumix S5, and Fujifilm X-T4). The results of the study show that technical specifications and functionality features have the highest weight. Sony A7 III ranked first with a preference value of 0.610, followed by Canon EOS R6 (0.581), Fujifilm X-T4 (0.472), Nikon Z6 II (0.401), and Panasonic Lumix S5 (0.368). This study proves the effectiveness of the AHP-TOPSIS method in making optimal camera purchase decisions and can be a reference for similar companies in determining the investment of photography and videography equipment according to operational needs

The integration of solar powered IoT irrigation systems in precision agriculture offers a sustainable solution to address water scarcity and enhance crop productivity. By leveraging real time data from soil sensors, weather APIs, and machine learning algorithms, these systems optimize irrigation schedules and improve water use efficiency. This research explores the potential of integrating renewable energy sources, such as solar power, with edge computing in smart irrigation systems to promote sustainable agricultural practices. The study aims to evaluate the performance of the proposed system in terms of water savings, crop yield, energy efficiency, and adaptability to varying climate conditions. Literature Review: Previous studies highlight the importance of smart irrigation systems in reducing water waste and improving crop yield through real time monitoring and automated decision making. However, existing systems often lack the integration of renewable energy and edge computing, which are critical for ensuring sustainability and operational efficiency in rural agricultural settings. The combination of renewable energy with IoT devices offers a promising solution to reduce energy costs and carbon emissions, while edge computing enhances real time data processing, ensuring prompt and accurate irrigation adjustments. Materials and Method: The proposed system integrates solar powered IoT devices, soil moisture sensors, weather data APIs, and edge computing devices to manage irrigation. Machine learning algorithms and evapotranspiration models are used to predict irrigation needs and optimize scheduling based on real time data. The system's performance is evaluated through metrics such as water savings percentage, crop yield improvements, and energy consumption, with a comparative analysis against traditional irrigation methods. Results and Discussion: The results indicate that the system successfully reduces water usage by 30% to 40%, increases crop yield by 25%, and operates with energy autonomy, powered entirely by solar energy. The system's adaptability to varying climate conditions ensures optimal crop growth, even under environmental stresses. The integration of renewable energy and edge computing significantly enhances the sustainability and efficiency of irrigation systems.

This study aims to evaluate the effectiveness of the Sea Toll Program, specifically Route T-26, with a focus on its outcomes and tangible benefits for the community in Fakfak Regency, West Papua. The research employed a descriptive quantitative method using statistical analysis through a paired sample t-test. Primary data were collected through field observations and interviews with relevant agencies such as the Directorate of Sea Traffic and Transportation and field implementation consultants, while secondary data were sourced from the 2024 operational report of Route T-26. Data collection techniques included field observation, primary surveys, document studies, and secondary data analysis. The findings indicate that the Sea Toll Program contributes to improving logistics distribution, lowering the prices of several key commodities, and reducing household expenditures, although statistical tests showed that the price differences were not significant. The implications highlight the need to optimize the volume and regularity of Sea Toll voyages to strengthen economic resilience in remote, outermost, underdeveloped, and border areas (3TP).

This study aims to analyze the suboptimal performance of hydraulic pump system on hatch cover performance on MV. Emerald Indah using USG (Urgency, Seriousness, Growth) method and data collection techniques in the form of observation, documents, and interview. The purpose of this study is to determine the causes, effect and efforts in solving the problems discussed. The results of the study indicate that several factors cause the hydraulic pump system to not function optimally , including dirty filters, leak in the hydraulic pump and pipe, and operation that is not in accordance with procedures. The effect of the suboptimal hydraulic pressure which ultimately becomes the main problem that inhibits the hatch cover opening process. To overcome this problem, improvements are needed such as periodic filter cleaning, replacement of leaking components, and increasing crew understanding of operational procedures. This research is expected to provide insight for related parties in improving the performanceof the hydraulic pump system and the efficiency of the loading and unloading process on ships.

This study discusses the arrangement of queue lanes in the supervision of weighing freight transportation at UPPKB Singosari to improve service efficiency. Based on the analysis of the Minimum Service Standards (SPM), three main indicators, namely compliance, conformity, and implementation, have reached 100%, while the accuracy indicator has only reached 50% due to the duration of weighing exceeding the set time limit. The main factor causing long queues is the lack of clear lane markings, making it difficult for vehicles to be directed without an officer. In addition, the parking area of 3,330.6 m² has not been utilized optimally. Improvement efforts include the implementation of queue lane markings to reduce dependence on officers, optimization of facilities such as Pos 2 which is parallel to Pos 1, and improvement of human resource management to suit operational needs. The use of Weight in Motion (WIM) technology is also recommended to reduce workload and accelerate the supervision of freight transport vehicles. By implementing this strategy, it is hoped that services at UPPKB Singosari can be more efficient, transparent, and in accordance with applicable standards.

This study aims to analyze the causes of data duplication in companies, its impact on operational efficiency, and the solutions that can be implemented to prevent and address it. Using a qualitative method with a library research approach, this study examines various literature related to data management. The findings indicate that data duplication is caused by a lack of standardization, input errors, and weak integration systems. The recommended solutions include the implementation of database management technology, regular data audits, and strict data governance policies. With the right strategies, companies can enhance efficiency and ensure data accuracy in business decision-making.  

The transformer is an important component, and early detection of potential failures plays an important role in the reliable operation of the electric power system. This article describes a new approach to power transformer failure prediction based on dissolved gas analysis (DGA) by applying the TDCG method with  the Random Forest algorithm. DGA data from operational transformers is used to train and test predictive models. The random forest  method based on TDCG allows comprehensive analysis of changes in dissolved gases in transformer oil, thus enabling early detection of failure conditions. The experimental results show that  the prediction model uses a model created by applying hyperparameter tuning for optimal  parameter tuning to have high accuracy, accuracy is obtained up to 96% in detecting potential failures, the standard used for accuracy presentation uses confusion matrix as the accuracy of the prediction model. In addition, it can optimize time efficiency in analyzing failures and prevent human error when calculating gas fault  identification or potential failures.

This study aims to evaluate the performance of the Sewage Treatment Plant (STP) at PT PLN Nusantara Power Unit Pembangkitan Gresik in reducing pollutant loads from domestic wastewater. The evaluation involves analyzing water quality parameters including pH, BOD, COD, TSS, oil and grease, total ammonia, and total coliform at both inlet and outlet of the STP. Additionally, the actual daily discharge was observed and compared to the design capacity to assess operational efficiency. The method used was descriptive qualitative, involving field observation, documentation, and laboratory test data analysis during the January–March 2025 period. The results show that all outlet parameters met the effluent standards set by Regulation No. 68/2016 of the Ministry of Environment and Forestry. However, the actual flow rate, which is only 1.6–3.3% of the design capacity, indicates potential inefficiencies in energy use and biological processes. Therefore, operational adjustments and optimization of STP capacity utilization are necessary for more efficient and sustainable system performance.

This research was made to examine the determinants of financial performance of banking companies in Indonesia. There are four independent variables (board of diversity, net interest margin, operational efficiency, and liquidity risk) and a moderating variable (firm size) have been analyzed in this research. Testing the interaction effect of firm size in explaining the influence of these four independent variables on banking financial performance is still very limited. This quantitative research was analyzed by using secondary data from audited annual reports of the company. The purposive sampling technique was used to choose the research’s samples during the observation periods (2018-2022) and obtained 200 observations (40 samples over 5 years of research). Panel data regression with the EViews program was used to test the eight hypotheses which was developed in this research. The results of the Chow test and Hausman test confirm the use of the Random Effect Model in the analysis. The findings from testing the interaction model show that firm size does not moderate the influence of board of diversity and net interest margin on financial performance, while for operational efficiency and liquidity risk variables, the firm size shows a pure moderating role for the both.

Garbage become problem complex in life urban areas , especially in Medan as Mother city North Sumatra Province . Research This analyze impact management Trash in Place Disposal End (TPA) Terjun , Medan Marelan District , regarding environment surrounding area . Method study use approach qualitative with technique observation , interviews , and studies documentation . Research results show that TPA Terjun has​ area 14 hectares Not yet managed optimally , with the dominant open dumping system . The impacts that arise covering groundwater pollution , pollution​ air , disturbance aesthetics , as well as improvement vector disease . Findings This reinforced by BPS data (2018) which shows density Medan 's population reached 8,342 people /km², correlated with high volume of waste . Research This recommend implementation system management rubbish integrated based on principle health environment and economy circular For reduce impact negative .

This study conducts a systematic literature review (SLR) exploring the Impact of Enterprise Resource Planning (ERP) and Big Data technologies in Improving Business Performance across global sectors. In the context of Industry 4.0, businesses are rapidly adopting the latest systems for operational efficiency. Research shows that ERP significantly improves business performance in various aspects, resulting in significant benefits for companies. Big Data is recommended as a tool for improving business processes; when combined with ERP, it enables effective and efficient production of useful outputs for companies. This SLR brings together a variety of articles from 2019-2025 and highlights a significant positive correlation between ERP, Big Data, and Business Performance of Companies. Although the relevance of these technologies is recognized, discussions on this topic in Indonesia are still limited. This study aims to encourage a deeper understanding and further research on ERP and Big Data.

Pressure vessels are critical components in the energy industry, used to store and process high-pressure fluids. The structural reliability of these vessels plays a pivotal role in ensuring operational safety and system efficiency. This study aims to analyze the design and reliability of pressure vessels using both numerical and experimental approaches to optimize performance and enhance safety factors. The numerical method was conducted through Finite Element Analysis (FEA) using ANSYS software to evaluate stress distribution, stress concentration, and potential failure modes under various operational load scenarios. Meanwhile, the experimental method involved hydrostatic pressure testing, strain measurements using strain gauges, and displacement analysis to validate the numerical simulation results. Data were collected from simulations and laboratory experiments, then analyzed quantitatively by comparing key parameters such as stress distribution, deformation patterns, and safety factors against industry standards. The results indicate that combining numerical and experimental approaches improves the accuracy of pressure vessel behavior predictions, enables more efficient design optimization, and enhances structural reliability. In conclusion, the methods applied in this study can serve as a reference for developing safer, more efficient pressure vessel designs that comply with industrial standards, thereby supporting improved safety and operational efficiency in the energy sector.