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Skincare Distributor Sr12 is a Distributor that provides herbal beauty products from PT. SR12 Herbal Perkasa. PT. SR12 Herbal Perkasa is a company engaged in the field of herbal & skin care which was established in 2015 by Toni Firmansyah, S. Farm., Apt as the main director, Asrianty Salam, S.Farm as a pharmacist who is responsible for Plant Operational. The Sr12 Distributor Store requires more active and wider marketing to increase sales. To improve marketing, an information system is needed that can make it easier for consumers to find information about product information and marketing of sr12 products. One of the media that is widely used in marketing is a website. A website is a collection of addresses that display interrelated information in the form of text, images, videos, animations, sounds or a combination of all of them that can be accessed using the internet. To build a website, a method is needed. Personal Extreme Programing (PXP) is a software development method that tries to simplify the various stages in the development process so that it becomes more addictive and flexible. Keywords: Information systems, single level, Personal Extreme Programming (PXP)

This research aims to develop and implement the design and front-end transition of a web-based admin dashboard to facilitate information access and support digitalization at PT Kalbe Farma Tbk, particularly in managing the weekly production schedule. The main issue faced is that the preparation of weekly production schedules at PT Kalbe Farma Tbk is still conducted manually using paper and spreadsheets, making it prone to errors and inefficiency. Established in 1966, PT Kalbe Farma Tbk has become a leader in Indonesia's pharmaceutical industry, with a strong commitment to innovation and quality. In addressing modernization challenges, the company seeks to enhance operational efficiency through advanced technology implementation. The platform was developed using the Laravel framework and Tailwind CSS, with PostgreSQL as the database. Key features of the platform include production scheduling, approval submissions, real-time schedule adjustments, and informative data visualization. This research focuses on implementing interface design, transitions, and page routing to improve employee productivity, expedite schedule approvals by production managers, and simplify schedule adjustments by warehouse staff, while reducing errors and improving information accuracy. The methodology used in this study is Rapid Application Development (RAD), which allows for rapid and flexible development with user involvement at every stage. The research also addresses system architecture, implementation processes, and the integration of key features, as well as testing to ensure the platform is accessible across various devices and browsers. The results of this research are expected to significantly contribute to improving operational efficiency and the competitiveness of PT Kalbe Farma Tbk in the pharmaceutical industry.

Belawan Port as the main port in Indonesia plays an important role in international trade. The Main Harbormaster and Port Authority Office (KSOP) of Belawan has the authority to supervise operational activities at the Port including regulating stevedoring workers (TKBM). This regulation is implemented through the TKBM Monitoring System (SIMON TKBM) to manage workers efficiently, transparently, and safely. This study uses a qualitative descriptive approach with literature study methods, interviews, observations and documentation then analyzed using data reduction methods, data presentation and drawing conclusions. The results of the study showed that the role of KSOP is very central in regulating TKBM through SIMON TKBM which includes TKBM supervision, competency improvement, rule enforcement, and coordination with stakeholders. However, technical obstacles were also found including the failure of duplicate data management and the absence of an automatic age filter in the system, as well as practical obstacles, namely the lack of coordination regarding TKBM competency certificates.

The role of school administration is very important in carrying out the basic functions of Islamic educational institutions. School administration as the center for managing teaching and learning activities also covers various fields ranging from resource management, financial management, to planning and implementing academic policies. This research aims to identify the role of school administration in improving the operational effectiveness and quality of Islamic education. The method used in this research is library research, which aims to collect, analyze and compile information from various literary sources in order to obtain a comprehensive understanding of the topic being researched. The data analysis technique used is descriptive-qualitative, with the aim of describing and interpreting information obtained from the literature. This research shows that the role of school administration is very important in improving the operational effectiveness and quality of Islamic education. Good administration includes technical management, creating an environment that supports the moral and spiritual development of students. With effective implementation, it is hoped that schools will be able to provide Islamic education that is not only of academic quality, but can also shape students' character in accordance with Islamic values. It is hoped that this research can become a reference for policy makers and Islamic education practitioners in formulating better management strategies, so as to improve the overall quality of Islamic education.

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.

The port industry plays an important role in Indonesia's economic growth, but its operational activities pose a major risk to occupational safety and health (OHS). The aim is to analyze the management of occupational accident risk hazards at Tanjung Perak Port. And identify potential hazards in loading and unloading activities, use of heavy equipment, and worker safety. This study was conducted qualitatively, which showed that several risks were in the low category with 2 risks, medium with 25 risks, and high with 12 risks, so that these results require immediate control measures. The application of OHS management through the HIRARC method helps to systematically identify, assess, and control hazards. This study suggests increasing compliance with the use of personal protective equipment (PPE), optimizing work procedures, and regular safety training to significantly reduce occupational accidents.

This literature review presents a synthesis of the latest research results regarding temperature measurement techniques, including sensor technology, calibration methods, and their applications in various industries. This analysis highlights advances in the use of infrared thermometry, thermocouple-based systems, as well as digital temperature monitoring tools. Key innovations in this field include real-time temperature monitoring with IoT integration, artificial intelligence (AI)-based predictive modeling, as well as increased accuracy through statistical calibration methods. This study shows that non-contact temperature measurement methods are increasingly important, especially in industrial and medical applications. In addition, the research also highlights the influence of environmental factors on temperature measurement accuracy as well as various strategies to overcome obstacles in using sensors in various operational conditions.

This study aims to analyze the effectiveness of Standard Operating Procedure (SOP) training on improving employee work competencies at PT Prima Sejati Sejahtera, a manufacturing company located in Central Java. SOP training that is organized in a structured and routine manner is expected to improve the quality of employee performance in accordance with applicable operational standards. This research uses a qualitative approach with data collection techniques in the form of in-depth interviews with employees involved in SOP training. The results of the study showed challenges such as unequal understanding between employees, time constraints, lack of in-depth interaction during training. Nonetheless, the training was still influential in improving employee competence and performance, although there were some barriers that affected its effectiveness. Therefore, the company needs to evaluate and improve the training materials, methods, and time so that it can be more optimal in improving the quality of employee performance.

MSMEs face complex challenges in building brand equity and customer loyalty in the digital era, where global competition and dynamic consumer preferences require innovative marketing strategies (Lasrado et al., 2022). This research aims to analyse the role of experiential marketing in improving brand equity and customer loyalty of MSMEs in international markets, with case studies on the creative sector (fashion/culinary) in three regions: ASEAN, Middle East, and Europe. Using an explanatory quantitative approach, data was collected from 400 active customers through a structured questionnaire and analysed with SEM-AMOS. Results show experiential marketing has a significant effect on brand equity. Practical implications include data analytics-based budget allocation recommendations and cultural adaptation in marketing strategies. The findings contribute to the global MSME digital marketing literature and offer operational guidance for businesses.

In the face of increasingly intense business competition, improving operational performance has become a critical priority for companies. One widely adopted strategy to achieve efficiency is the Just In Time (JIT) system. This study applies a Systematic Literature Review (SLR) method to analyze the impact of JIT implementation on companies' operational performance. The findings reveal that JIT significantly contributes to reducing storage costs, enhancing production efficiency, speeding up distribution processes, and increasing operational flexibility and customer satisfaction. However, the success of JIT implementation largely depends on effective coordination with suppliers, technological readiness, and the competence of human resources.

This study examines the adaptive strategies employed by small and medium-sized enterprises (SMEs) in Shenzhen in response to the decoupling trend associated with the new US tariff policy. Given the' increasing complexity and unpredictability of international trade dynamics, Shenzhen SMEs must innovate and diversify their operational approaches to sustain competitiveness. The re-search highlights the significance of enhancing innovation capabilities, which enable SMEs to de-velop new products and services that meet shifting market demands. Additionally, the study empha-sizes the importance of market diversification and supply chain flexibility, allowing SMEs to miti-gate risks related to tariff impacts. Collaborative networks facilitate resource sharing and knowledge exchange, further bolstering adaptability. The findings indicate that by fostering a proactive entre-preneurial orientation and engaging with policymakers, Shenzhen SMEs can effectively navigate the challenges posed by the US tariff policy, ensuring long-term sustainability and growth in a competi-tive landscape through a sample of 190 SMEs in April of 2025.

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 purpose of this study is to analyze the implementation of Database Management System (DBMS) in improving the operational efficiency of companies. This study uses a qualitative research method through a literature review, where various academic sources and literature are analyzed to identify the benefits, challenges, and impacts of DBMS implementation on operational efficiency. The results indicate that DBMS helps in structuring data management, enhancing data security, and accelerating decision-making processes. Future research is suggested to conduct empirical studies with a quantitative approach to measure the impact of DBMS implementation more specifically across various industrial sectors.

One form of implementation of the Tri Dharma of Higher Education is industrial visit activities for the application of science, including industrial visits at the international level. This industrial visit was conducted at JJ Ardon Transport, located in Goes City, Zeeland, The Netherlands. This article aims to analyze the benefits and impacts on the enrichment of management knowledge and corporate management strategies at the global level applied to the companies visited. The methods used include direct observation, in-depth interviews, and documentation of operational practices in the company. The results of the discussion show that management practices, implementation of business strategies and modern technology have been implemented by JJ Ardon Transport and can be a reference for the management of similar companies in Indonesia. This article also provides recommendations for the implementation of the results of the visit in the development of higher education curricula and strengthening international collaboration.

The rapid growth of e-commerce has driven companies to seek more effective strategies to enhance logistics efficiency and customer satisfaction. This article examines the synergy between artificial intelligence, strategic location determination, and digital marketing in supporting the performance of digital supply chains. This multidimensional approach demonstrates that integrating cutting-edge technologies with precise location strategies and data-driven marketing can create superior customer experiences and more efficient operational costs. This study is based on a literature review of ten recent related studies. Moreover, it highlights consumer behavior shifts due to the digitalization and globalization of supply chains.  

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.

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.

This study explores the integration of AI-driven process optimization in Waste-to-Energy (WtE) systems to enhance urban sustainability. The research focuses on designing a gasification-based WtE system, incorporating AI predictive control to optimize energy conversion processes. The AI system adjusts operational parameters in real-time, improving energy conversion efficiency by 25% and reducing carbon emissions by 40%. Additionally, the system's waste-to-energy conversion rate is projected to increase by 20%, and operational costs are expected to decrease by 30%. Data collection and analysis are carried out using advanced sensors to monitor key parameters such as temperature, gas composition, and energy output, which are then processed by machine learning algorithms for predictive analysis. The results show that the AI optimization significantly enhances system performance, offering a sustainable solution for urban waste management. The study highlights the technical and operational challenges of integrating AI into existing WtE systems, including the need for infrastructure upgrades and scalability considerations. It also discusses the socio-economic impacts, including job creation, reduced energy costs, and improved public health. The findings demonstrate the potential of AI-based WtE systems in reducing waste, generating clean energy, and mitigating climate change, positioning them as a viable solution for sustainable urban development.

The loading and unloading process involves moving goods from one place to another, often requiring specialized equipment such as a wire crane. In maritime operations, unexpected incidents like wire crane breakage can occur. Wire crane breakage refers to damage in the sling wire of a ship's crane, reducing its lifting capacity and causing the wire fibres to unravel. During sea-based fieldwork on the MV. Pacific Bulk, researchers observed a wire crane failure during loading and unloading operations, which caused delays and financial losses. This study aims to identify the causes of wire crane breakage on the MV. Pacific Bulk and examine its technical and operational impacts. Using a qualitative descriptive method and fishbone analysis for data interpretation, the study found several contributing factors: wire corrosion, crane age, lack of standard operating procedures (SOPs) for crane maintenance, insufficient crew, inadequate maintenance, lack of routine inspections, and challenging environmental conditions. The research also highlights the technical and operational consequences of such failures, including delays and economic loss. To address the issue, the study suggests implementing scheduled periodic inspections following SOPs, applying regular lubrication, and maintaining data records of the wire crane’s lifespan. These preventative measures aim to improve operational efficiency and avoid future wire crane failures.

Fire incidents in Indonesia remain relatively high, with a total of 2,286 cases recorded. In 2022, the frequency of fires in Jakarta reached 1,691 cases, marking a 10% increase compared to the previous year, which had successfully reduced fire frequency by 23%. The high fire risk in high-rise buildings can lead to both material losses and casualties. This study aims to design the layout and determine the requirements for portable fire extinguishers  in a hospital project in Jakarta. The design of the fire extinguisher layout and requirements is intended for the operational phase of the building, ensuring optimal applicability. The location, area, and/or environment with various work activities and risk levels ranging from low to high indicate that safety is of paramount importance and must be prioritized, and that any form of accident should be addressed as early as possible. This research employed a qualitative descriptive method to describe and illustrate existing phenomena, both natural and human-engineered, through observation, interviews, and documentation. The findings show that the design of the fire extinguisher layout and requirements amounted to 61 units across the 4th to 7th floors, with the fire extinguisher layout plan attached. The type of fire extinguisher used on each floor is a 6-kg dry powder extinguisher. The conducted fire risk assessment indicates that each floor presents a moderate hazard, while some rooms exhibit a high hazard level. This study provides recommendations for the placement and requirements of fire extinguisher in accordance with standards and is expected to contribute to fire prevention efforts in the hospital project in Jakarta once it becomes operational.