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This research examines the role of SIMKARI (Sistem Informasi Manajemen Kejaksaan) in enhancing transparency and accountability at the High Prosecutor’s Office of Gorontalo in the digital era. The implementation of SIMKARI, as a digital management information system, is aimed at improving the efficiency of data management, monitoring, and reporting within the institution. Through qualitative research methods including literature study, observation, and interviews with key stakeholders at the High Prosecutor’s Office of Gorontalo, this study identifies both the benefits and challenges associated with SIMKARI's use. The results indicate that SIMKARI has significantly contributed to the transparency of public information and the accountability of internal performance. However, challenges such as limited digital literacy and infrastructure issues remain. The study concludes that continuous improvement and strategic collaboration are necessary to optimize SIMKARI’s effectiveness in supporting a transparent and accountable justice system.

The rapid development of information technology has accelerated the transformation of public services in Indonesia toward digitalization. This study aims to analyze the effectiveness level of digitalization in administrative services at the Medan Amplas District Office. A qualitative approach was used, employing a literature review method by collecting data from books, scientific journals, policy documents, and institutional performance reports. The results show that the digitalization of administrative services in Medan Amplas District has improved service timeliness, cost and procedure transparency, and public satisfaction, with system adoption rates increasing from 30% to 65% between 2018 and 2022. Digitalization has also provided benefits in terms of time and cost efficiency, as well as enhanced staff productivity. However, several challenges remain, such as infrastructure limitations, uneven digital competencies among staff, regulatory inconsistencies, and organizational culture resistance to change. In conclusion, the digitalization of administrative services at Medan Amplas District has been effective but still requires continuous improvement in technical aspects, human resource capacity building, regulatory harmonization, and cultural change to achieve sustainable optimization of public services.

The detection of hazardous gases, such as carbon monoxide (CO), is crucial for ensuring human safety and health, especially in enclosed environments or areas with a high potential for exposure to toxic gases. Carbon monoxide is a colorless, odorless gas that is extremely dangerous when inhaled in large amounts. Therefore, a CO detection system that can provide early warnings is essential. This research aims to design a carbon monoxide (CO) detector using the MQ-7 sensor, which can detect CO concentrations in the air. The detection system is developed based on Internet of Things (IoT) technology, enabling real-time CO detection data to be transmitted to a cloud platform or user devices via an internet connection. This allows users to monitor CO levels in their environment anytime and anywhere. The system consists of the MQ-7 sensor to detect CO levels, a microcontroller as the controller, and a communication module to send data to the internet. The main advantage of this system is its ability to notify users if CO levels exceed a safe threshold. Thus, this detector can function as a preventive tool against CO exposure accidents. The use of IoT in this system also facilitates remote monitoring, improving the effectiveness and efficiency of managing a safe environment.

The Occupational Safety and Health Management System (SMK3) has an important role in creating a safe and productive work environment, especially in the manufacturing industry which has high risk potential. This research uses a literature study approach to evaluate the concept, implementation, and impact of SMK3 on operational performance. The results show that consistent implementation of SMK3 can reduce the number of work accidents, improve the efficiency of the production process, and encourage the creation of a positive safety culture. However, several obstacles are still faced, such as low awareness and compliance with safety procedures and weak supervision. Therefore, the active involvement of all parties, from management to employees, as well as regulatory support from the government is needed to ensure the effectiveness of SMK3 in the long term and improve industrial competitiveness.

This community service activity is a tangible form of the university's commitment to answering the challenges of the digital era. The issue and focus of this community service is that it is known that the manual attendance method that is still used by teachers is less effective in recording attendance, entry time, and lateness. Therefore, this study aims to implement a digital attendance information system to improve the accuracy and efficiency of attendance recording. Teacher training at Al-Imam Islamic School Junior High School aims to improve the student attendance system with an Android-based approach using AppSheets and Spreadsheets. The implementation of training on making an android-based student attendance information system with appsheets and spreadsheets at Al-Imam Islamic School Cileungsi Junior High School proved that teachers showed an increase in understanding related to the concept of making information systems, appsheets and spreadsheets, which included camera features, GPS, updated data in spreadsheets, to procedures for making applications using spreadsheets. Teachers learn that the attendance information system is not a difficult thing and in this day and age we are also required to enter the world of technology and digital to make teaching and learning activities easier and more fun, This increase in understanding is reflected in the results of pre-test evaluations and material presentations that show an increase in knowledge in understanding the concept of creating an android-based student attendance information system with appsheets and spreadsheets.

The use of Big Data Analytics (BDA) in the financial audit process has altered the traditional audit method by improving audit quality and efficiency. The purpose of this study is to critically assess BDA's role in reducing audit delays and increasing audit quality. Using a literature review approach, this study intends to consolidate findings from national and international studies published between 2017 and 2024 that focus on the role of BDA in audit procedural transformation, fraud detection, and real-time decision support. The findings reveal that BDA not only allows auditors to review massive amounts of data in real time, but it also improves evidence collection and risk assessment. Audit delay has emerged as a significant variable in the relationship between BDA and audit quality, however its effectiveness varies depending on technical infrastructure and auditor expertise. Furthermore, this study identified implementation problems for BDA, such as data security threats, technology literacy gaps among auditors, and organizational readiness, all of which must be addressed in order for BDA to reach its full potential. This study adds to the theoretical and practical discussions about the strategic use of BDA to alter audit methods in the digital era.

This study investigates the role of adaptive leadership in addressing the complex challenges posed by rapid technological advancements, particularly in the era of Society 5.0. The integration of artificial intelligence (AI) into organizational systems introduces not only opportunities for efficiency and innovation but also ethical and leadership dilemmas. Using a literature review methodology, this paper examines how adaptive leadership can support organizations in navigating digital transformation while maintaining ethical integrity and organizational effectiveness. The findings indicate that adaptive leadership—characterized by responsiveness, inclusivity, and value-driven decision-making—is essential for sustaining organizational resilience. Furthermore, the study emphasizes the need for leaders to foster a learning-oriented culture, manage ethical concerns in AI deployment, and apply flexible leadership styles that empower employees. This paper contributes to the growing discourse on ethical digital leadership and offers insights for organizational sustainability in the context of technological disruption.    

Research aims to design and develop a boiler system for heating Marine Fuel Oil (MFO) 180 CST by integrating Internet of Things (IoT) technology to enhance efficiency and operational monitoring. The methods used include boiler system design, selection of types and materials according to international standards, and the implementation of an optimal combustion system. IoT sensors are strategically placed to monitor key parameters such as temperature, pressure, and fluid flow in real-time. The collected data is transmitted to a cloud platform, enabling remote monitoring and automated performance analysis through a web or mobile-based application.. The research results indicate that IoT integration in the boiler system improves fuel heating efficiency, optimizes energy consumption, and facilitates easier monitoring and process control. Testing includes pressure tests, combustion efficiency, steam capacity, and material durability, with real-time monitoring to support performance analysis and early problem detection. Operational data evaluation allows for design adjustments or system settings to further enhance energy efficiency. With this innovation, the boiler system can operate more optimally, support energy efficiency, and facilitate predictive maintenance for sustainable industrial operations. The implementation of IoT in this system is expected to improve safety, effectiveness, and automation in boiler management, making it a more reliable and modern solution.

This study aims to analyze the implementation of management control systems in improving company performance at PT. Melu Bangun Wiweka (MBW), a private construction company facing tight competition in the construction services industry. The study uses a qualitative approach with a descriptive method, where data is obtained through interviews with the company. The results of the study indicate that PT. MBW has implemented a fairly good management control system through the stages of strategic planning, budgeting, activity implementation, and performance evaluation. This system has been proven to play an important role in directing organizational activities and improving employee performance through the provision of rewards and sanctions based on standard operating procedures. This study concludes that a structured and communicative management control system can improve the effectiveness and efficiency of the company in achieving its goals. It is recommended that the company continue to improve employee understanding of the company's vision and strengthen the evaluation system to face competitive challenges in the future

This article aims to analyze the differences in stock performance before and after mergers and acquisitions in companies listed on the Indonesia Stock Exchange (IDX). The problem focuses on the impact of mergers and acquisitions on stock performance indicators, such as Stock Returns, Price Earnings Ratio (PER), Price to Book Value (PBV), and Earnings Per Share (EPS). In order to approach this problem, theoretical references from financial management and market efficiency theory are used. Data were collected through financial statements of companies undergoing mergers and acquisitions in the 2018-2020 period and analyzed quantitatively using normality tests and significant difference tests with paired sample t-tests. This study concludes that mergers and acquisitions have a significant effect on increasing several stock performance indicators, especially Stock Returns and PBV, although the impact on PER and EPS varies depending on the industry sector and market conditions. The results of this study are expected to provide insight for investors and business actors in assessing the effectiveness of mergers and acquisitions as a company growth strategy.

This study presents a computational analysis of a corn drying system using SolidWorks simulation tools. The main objective is to understand the thermal and flow behavior within a silo-type corn dryer powered by a wood-fueled horizontal furnace. The simulation covers thermal distribution, air velocity, and flow trajectories using finite element analysis and computational fluid dynamics (CFD). The model includes a vertical silo with embedded piping systems and air inlets driven by blower-induced convection. The heat source, simulated at 500°C from the furnace, is transferred through ducts into the drying chamber. The results indicate that air temperature reaches up to 100°C within the chamber with a velocity of up to 5 m/s. Temperature and velocity distributions show a good potential for uniform drying, although lower regions exhibit heat accumulation. These findings highlight the effectiveness of the system design in enhancing drying efficiency.

This study aims to design and build a hydraulic system capable of operating hatch opening and closing automatically and manually, with the application of Internet of Things (IoT) technology to monitor and control the system remotely. This system is designed to improve efficiency and ease of hatch operation on ships or other industrial applications, as well as prevent fires in cargo due to several factors such as unintentional negligence of the ship's crew and also weather factors with increasing temperatures. Where the automatic system uses a rain sensor to optimize time and energy, while manual control remains available as a backup option. This design involves the integration of hydraulic actuators, rain drop sensors, microcontrollers, and IoT communication modules that allow users to control and monitor the position of the hatch through a web-based application or mobile device. In compiling this scientific paper, researchers use experimental methods. This study shows the results that testing will be carried out directly by researchers, by testing the performance of the prototype of the automatic and manual hatch opening and closing hydraulic system design tool based on IoT by testing the effectiveness of the control system and sensor performance. In conclusion, this system successfully combines hydraulic and IoT technology to create an efficient, safe, and easy-to-use solution in practical applications.

The city of Palembang, traversed by the Musi River, is well suited for industrial development in the fisheries sector. The area is renowned for its distinctive regional cuisine, one of which is pempek which is a processed fish product. Entrepreneurs supporting the supply of raw materials for processed fish products include ground fish businesses. The ground fish industry continues to expand, with business owners striving to maintain and enhance product quality and service standards to remain competitive and promote growth. In this regard, the decisions made by leaders significantly impact an organization’s ability to achieve its objectives. Therefore, appropriate methodologies are required to analyze the key factors influencing success or failure. SWOT analysis helps identify external opportunities and threats as well as internal strengths and weaknesses. Additionally, CSF analysis provides a clearer interpretation of key elements, defines essential activities, and supplies relevant information. Furthermore, this research proposes strategies to enhance efficiency, effectiveness, and value at every stage of the value chain. It is expected that this analysis will assist businesses in optimizing resources and improving the competitiveness of ground fish enterprises in the market. This study aims to provide a comprehensive analysis of strategic measures that can enhance the competitive advantage of ground fish businesses in the fisheries and food processing sectors.

This study aims to analyze the effect of the implementation of the Core Tax Administration System (CTAS) in Indonesia on tax revenue performance, specifically on the efficiency of employee performance at the Directorate General of Taxes through qualitative approach methods. The sample collection technique used purposive sampling where respondents were determined with the criteria of being employees at the Directorate General of Taxes with the position of Tax Executor and Counselor. Coretax, as a digital technology-based tax system, is expected to increase the transparency of tax information and strengthen the supervision mechanism in tax management. This study aims to show that the implementation of Coretax contributes significantly to increasing the effectiveness of employee performance at the Directorate General of Taxes and strengthening the ability of tax authorities to search for transaction data, reduce opportunities for fraud, and accelerate the audit process of tax cases. The results of the study show that Coretax is able to improve service performance faster, more efficiently and transparently and. However, the challenges in implementation practice from early January 2025 to the end of April 2025 still have system error problems that do not always run smoothly and a series of other technical problems, both from the user interface of taxpayers and tax officers themselves.  

This study aims to analyze the implementation of the 4P marketing mix strategy (Product, Price, Place, Promotion) at Firdaus Farm, a tilapia farming business in Tasikmalaya, and its effectiveness in enhancing the business's competitiveness and profitability. The method used is qualitative descriptive with a case study through observations, interviews, and direct documentation at the business location. The research findings indicate that the product strategy, which emphasizes tilapia quality—such as freshness, uniform size, clean packaging, and quality certification—constitutes the primary factor in attracting consumer interest. The flexible and competitive pricing strategy, adjusted according to market conditions and consumer purchasing power, along with bonuses for loyal customers, proved to increase customer loyalty and sales. Product distribution is carried out through traditional channels and has begun utilizing digital platforms to expand market reach, with the strategic location of the business supporting distribution efficiency. Promotion, still mainly traditional, is starting to develop into digital promotion through social media, which effectively increases product visibility and appeal. This study concludes that the consistent and adaptive application of the 4P marketing mix can enhance Firdaus Farm’s competitiveness in the tilapia market. It is recommended that business practitioners continue to develop product innovations, evaluate pricing, expand digital distribution, and optimize digital promotion in order to face increasingly intense market competition.

Local financial management in Indonesia still faces significant challenges, such as budget inefficiencies, high dependence on central funds, and lack of locally generated revenue (PAD), which exacerbates development inequality, especially in underdeveloped regions such as Papua. This research highlights the importance of cross-sector collaboration and technology utilization for the optimization of local finance to achieve sustainable development equity. Collaboration between central and local governments, the private sector, and the community can improve transparency and accountability of budget management, while technologies such as e-budgeting, blockchain, and the Local Government Information System (SIPD) can accelerate the budget planning and monitoring process. This study uses a descriptive qualitative approach with thematic analysis of primary and secondary data to evaluate the effectiveness of technology integration and cross-sector collaboration. The results show that a strong synergy between collaboration and technology can improve budget efficiency, reduce dependency on central funds, and accelerate infrastructure development and public services in disadvantaged areas. Policy recommendations include strengthening local government capacity, implementing a blockchain-based monitoring system, and involving communities in development planning. This research contributes to the local financial management literature by offering evidence-based solutions that support inclusive and equitable development in Indonesia.

This study aims to analyze the influence of accountability, transparency, rule of law, effectiveness, and efficiency on local government performance with supervision as a moderating variable in the Langkat Regency Government. This study uses an associative research method with a quantitative approach based on numbers. The study population consisted of 40 Regional Work Units (SKPD) with 120 respondents determined through purposive sampling techniques, with the criteria of heads of departments/agencies, secretaries, and treasurers who have served for at least the last five years. Primary data were obtained through distributing questionnaires using a Likert scale, and data analysis was carried out with the help of SmartPLS 4.0 software. The results of the study indicate that the variables of accountability, transparency, rule of law, and effectiveness and efficiency have a positive and significant effect on local government performance. However, the results of the moderation test indicate that supervision only plays a significant role as a moderating variable in strengthening the relationship between the rule of law and local government performance. Meanwhile, supervision does not significantly moderate the relationship between accountability, transparency, and effectiveness and efficiency on local government performance. These findings are expected to be a consideration for local governments in improving the quality of governance, especially through strengthening the rule of law supported by an effective monitoring system.

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.

Aquaculture is a vital sector in global food production, providing essential protein sources. However, the industry faces significant challenges, including high energy consumption and environmental impact. The integration of renewable energy, particularly solar power, with automation and IoT systems offers a promising solution to enhance energy efficiency, sustainability, and productivity in aquaculture operations. This study aims to evaluate the effectiveness of solar powered autonomous systems in reducing energy usage, improving operational efficiency, and promoting environmental sustainability in aquaculture. Literature Review: Recent research has explored various technologies, such as Digital Twins (DTs) and Precision Fish Farming (PFF), which integrate IoT sensors for real time monitoring and optimization of fish farming operations. The combination of Artificial Intelligence (AI) and the Internet of Things (IoT), known as AIoT, has further advanced the industry by enabling automated decision making and predictive analytics. Solar power integration with IoT systems has been shown to significantly reduce operational costs, minimize carbon emissions, and enhance the sustainability of aquaculture practices. These advancements have the potential to address the challenges of energy consumption and environmental degradation in the industry. Materials and Method: This research utilizes a hybrid solar powered IoT system for aquaculture, integrating solar panels, IoT sensors, and automated control systems. The system monitors key water quality parameters, such as pH, dissolved oxygen, turbidity, and temperature, to maintain optimal conditions for aquatic life. Data is collected through IoT sensors and analyzed through a cloud-based platform. A pilot study is conducted on a small scale aquaculture farm to evaluate the system's performance, including energy consumption, water quality management, and fish health. Energy savings, operational efficiency, and environmental impact are assessed. Results and Discussion: The integration of solar powered IoT systems significantly reduced energy consumption compared to traditional systems, with a notable decrease in grid electricity reliance. The system successfully maintained optimal water quality conditions, enhancing fish health and growth. Solar powered systems proved reliable, even in regions with variable sunlight, and demonstrated improvements in operational efficiency through automation. The environmental benefits were evident, with a reduction in carbon emissions and lower operational costs. The study highlights the feasibility of solar powered IoT systems as a sustainable solution for modern aquaculture operations.

Introduction: Achieving carbon neutrality in industrial systems is essential for mitigating climate change and promoting sustainability. The increasing demand for energy optimization and carbon emission reduction has driven the development of advanced technologies, particularly hybrid machine learning (ML) models. These models, combining ensemble learning and reinforcement learning (RL), offer significant promise in optimizing industrial processes, reducing energy consumption, and improving environmental performance. This study explores the application of hybrid ML models in achieving carbon neutral goals through dynamic process optimization and energy control in industrial settings. Literature Review: Hybrid ML models integrate different machine learning techniques to handle complex and dynamic environments effectively. Ensemble learning methods, such as boosting, bagging, and stacking, combine multiple algorithms to improve predictive performance and robustness. Reinforcement learning (RL), on the other hand, enables real time decision making and adaptation based on trial and error interactions with the environment. In energy optimization, these models are used to reduce energy intensity and carbon emissions, enhancing overall operational efficiency. Previous studies have demonstrated the effectiveness of ML models in energy management, but challenges such as data quality, model integration, and computational complexity remain. Materials and Method: The study applies hybrid ML models combining ensemble learning and RL to optimize energy consumption and minimize carbon emissions in industrial processes. Data from real time sensors and operational parameters are used to train the models. The ensemble learning component improves the accuracy of energy predictions, while RL ensures dynamic process adjustments in response to fluctuating energy demand. The models were tested in various industrial settings, including manufacturing processes, smart grids, and microgrid systems. Performance metrics such as energy efficiency, carbon emissions reduction, and operational costs were evaluated to assess the effectiveness of the models.  Results and Discussion: The hybrid ML models achieved significant reductions in energy intensity (15-20%) and carbon emissions (18-25%). The real time adaptability of the RL component allowed the models to adjust energy consumption patterns dynamically, improving energy efficiency and reducing waste. The models demonstrated their ability to adapt to varying operational conditions, ensuring optimal energy use. A cost-benefit analysis showed that the hybrid models provided substantial energy savings and reduced operational costs, with a return on investment (ROI) of 30-35% within the first year of deployment. However, challenges such as computational complexity and data quality issues were identified, highlighting the need for further refinement in model development.