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The development of artificial intelligence (AI) technology has influenced various aspects of human resource (HR) management, from recruitment, training, to performance evaluation. This article aims to theoretically examine the convergence between AI, human capital, and economic efficiency in the context of contemporary HR management. The method used is a literature study of recent scientific publications related to these topics. The results show that the integration of AI in HR management can improve operational efficiency and decision-making effectiveness, but still requires strengthening human capital capacity to be adaptive to technological changes. This article emphasizes that the success of HR management in the digital era depends on the synergy between smart technology and sustainable human capital development. Therefore, AI-based HR strategies need to be designed with human-centered principles to ensure increased productivity as well as organizational sustainability.   Perkembangan teknologi kecerdasan buatan (Artificial Intelligence/AI) telah memengaruhi berbagai aspek manajemen sumber daya manusia (SDM), mulai dari rekrutmen, pelatihan, hingga evaluasi kinerja. Artikel ini bertujuan untuk mengkaji secara teoretis konvergensi antara AI, human capital, dan efisiensi ekonomi dalam konteks manajemen SDM kontemporer. Metode yang digunakan adalah studi literatur terhadap publikasi ilmiah terbaru terkait topik-topik tersebut. Hasil kajian menunjukkan bahwa integrasi AI dalam pengelolaan SDM dapat meningkatkan efisiensi operasional dan efektivitas pengambilan keputusan, namun tetap memerlukan penguatan kapasitas human capital agar adaptif terhadap perubahan teknologi. Artikel ini menegaskan bahwa keberhasilan manajemen SDM di era digital sangat bergantung pada sinergi antara teknologi cerdas dan pengembangan human capital yang berkelanjutan. Oleh karena itu, strategi SDM berbasis AI perlu dirancang dengan prinsip human-centered untuk memastikan peningkatan produktivitas sekaligus keberlanjutan organisasi.

This study investigated the influence of financial report preparation skills, financial literacy, and accounting information systems on the performance of micro, small, and medium enterprises (MSMEs) in Cirebon Regency. The research adopted a quantitative approach with a causal associative design. Data were collected through closed-ended questionnaires distributed to 100 culinary-sector MSMEs selected using purposive sampling. The data analysis involved validity and reliability testing, classical assumption tests, and multiple linear regression. The findings revealed that financial report preparation skills, financial literacy, and accounting information systems had both partial and simultaneous positive effects on MSME performance. Specifically, the ability to prepare financial statements and the use of accounting systems significantly enhanced operational efficiency and financial outcomes, while financial literacy contributed to better financial decision-making. The study concluded that improving financial competencies and adopting technology-based accounting practices are key drivers for strengthening MSME performance in the region

The automotive industry is a strategic sector that plays a crucial role in national economic growth. Facing rapid digital transformation, automotive companies are increasingly adopting Business Intelligence (BI) systems to facilitate a data-oriented decision-making process. This study aims to explore the implementation of BI in XYZ, one of Indonesia’s largest car manufacturers. Using a descriptive qualitative approach through literature review, the research highlights how BI dashboards enable real-time analysis of vehicle sales trends, regional performance, and product models. The findings indicate that BI significantly enhances strategic planning, marketing accuracy, and operational efficiency. Visual tools such as Tableau provide centralized dashboards that facilitate faster insights, enabling companies to adjust production and distribution strategies based on data patterns. The study concludes that BI is not merely a visualization tool but a vital element of the digital transformation strategy in the automotive sector.

The purpose of this research is to examine how production costs factor into producer choices, particularly those pertaining to output volume, selling price estimation, and company growth strategies.  The research examined micro and small business players in Kediri Regency, East Java, employing a descriptive quantitative technique.  The findings demonstrate that the production cost structure, particularly the preponderance of variable costs, considerably affects the quantity of output and the margin for price adjustment.  It has additionally been demonstrated that saving money encourages manufacturers to take risks and grow their companies.  Moreover, management accounting-based cost tracking, waste reduction, and sourcing local raw materials are all cost management tactics that impact a company's strength and ability to compete.  Producers' long-term strategic decision-making is therefore influenced by effective production cost management, which in turn affects operational sustainability.

Data architecture is a framework that structures and manages data flows in an organization so that they can be used optimally to support data-based decision-making processes. The right design in data architecture ensures that data can be stored, accessed, processed, and analyzed efficiently. The main components in data architecture include data sources, storage systems, data processing, data integration, and analytics. In addition, aspects of security and data quality management also play an important role in maintaining data integrity and confidentiality. In the context of an ever-evolving business, data architecture must be able to adapt to changing organizational needs and existing technologies, as well as provide scalable and flexible solutions. Therefore, good data architecture management is a key factor in achieving operational efficiency and competitive advantage in the digital era.

This research was conducted at PTPN IV Regional II Adolina Palm Oil Plantation and Mill Unit with the aim of evaluating the effect of Ripple Mill machine efficiency on palm kernel impurity levels through a multiple linear regression analysis approach. Ripple Mill is a vital piece of equipment in the palm kernel cracking process, which plays a role in determining the quality of the palm kernel. This machine works by breaking the kernels to produce kernels that are separated from the shells. However, when machine efficiency decreases due to technical and operational factors, palm kernel impurity levels tend to increase, characterized by an increase in shell fragments, fibers, and other foreign materials. This condition can have an impact on decreasing product quality and increasing further processing costs. Data collection was carried out over five days of observations covering the variables of machine efficiency and kernel impurity levels obtained from production results. The study found a strong negative correlation between machine efficiency and impurity levels in palm kernels. This means that the higher the efficiency of the Ripple Mill, the lower the resulting palm kernel impurity levels. This finding also confirms that quality control in the production process is not only determined by raw material factors but also highly dependent on the performance of the processing machine. Furthermore, the research results demonstrate the importance of implementing preventive maintenance strategies, including regular inspections of the rotor bar, square bar, and drive motor, as well as regulating operating parameters such as rotational speed and machine load. Proper preventive maintenance and operational control are essential to sustain machine efficiency and product quality. Therefore, continuous improvement in technical and managerial aspects is essential to maintain palm kernel quality and support optimal palm oil mill productivity.

This study was conducted to analyze the effect of suction power effectiveness on cyclones in Light Tenera Dust Separator (LTDS) 1 and 2 units on the level of palm kernel losses at PTPN IV Regional II Plantation Unit and Adolina Palm Oil Mill (POM). Palm kernel loss is a significant factor that can reduce production efficiency, as palm kernel has high economic value and is the main product in the palm oil industry. Kernel losses not only reduce production efficiency but also create significant economic disadvantages for the palm oil mill. The research method used was a gravimetric method with a field experiment approach. The research process included sampling from LTDS waste, separating kernels from shells, and measuring suction speed using an anemometer to determine cyclone performance. The gravimetric method was applied to quantify the proportion of kernel mixed with shell waste, providing measurable data on suction efficiency. The results showed that low suction power effectiveness was directly proportional to the increasing number of kernels that were thrown away with the shells. In other words, poor suction performance directly correlates with higher kernel losses. The main contributing factors include leaks in the cyclone, suboptimal blower settings, and inadequate operator skills. Operational skills and equipment maintenance were identified as crucial determinants of system performance. Based on these findings, improvements to the suction system are recommended through routine maintenance, leak checks, and blower setting calibration. Furthermore, operator training is required to precisely adjust suction power. By maintaining suction effectiveness and optimizing blower settings, kernel losses can be reduced below the standard threshold of 2.0%. Thus, mills can improve operational efficiency while minimizing economic losses due to palm kernel loss.  

This thesis presents a conceptual analysis of the utilization of Unmanned Surface Vehicle (USV) technology to support the Indonesian Navy (TNI AL) in maintaining maritime security within the ALKI II (Indonesian Archipelagic Sea Lane II) region, in order to enhance operational efficiency and effectiveness. USVs are surface vessels that operate autonomously or are remotely controlled without onboard human presence. These vehicles can be operated from land-based control stations or from other vessels. The main research question addressed in this study is how the development and application of USV technology can support the Indonesian Navy’s mission in safeguarding maritime security within the ALKI II corridor. This study considers USVs as a surveillance asset, representing a technological advancement that can significantly enhance the Navy’s surveillance and monitoring capabilities. It is expected that the implementation of USVs will contribute to improved efficiency in securing and supervising ALKI II, while also promoting effective coordination among relevant stakeholders. Ultimately, the presence of USVs may help to reduce and prevent unlawful activities in the ALKI II waters. This research employs a qualitative methodology. The findings indicate that the use of USVs enhances both operational effectiveness and efficiency, thereby supporting the Indonesian Navy’s mission to secure the ALKI II region. This study aims to provide strategic recommendations to the Indonesian Navy regarding the development and integration of USV technology. It is anticipated that such measures will serve as a significant step toward reinforcing maritime security in the ALKI II corridor.

The Ripple Mill machine is one of the vital components in a Palm Oil Mill (PKS) that functions to separate the palm kernel from its shell. This process is very important because the quality and quantity of the palm kernel produced will directly affect the economic value and production efficiency in the palm oil industry. At PTPN IV Regional II Plantation Unit and Adolina PKS, various technical problems were found that caused a decrease in machine performance, including rotor bars and square bars that experienced wear due to age and improper machine settings. In addition, other damage that often occurs is a broken van belt due to age and excessive tension, feeder motor dysfunction caused by excessive load, and motor overheating that occurs due to age and high workload. To overcome these problems, this study uses the Failure Mode and Effect Analysis (FMEA) method. This method aims to identify various potential failures, assess the severity, frequency of occurrence, and detection capability, so that the Risk Priority Number (RPN) value can be calculated as a basis for repair priorities. The results showed that worn rotor bars and worn square bars had the highest RPN values, each at 280, equivalent to 40.23% of the total identified risks. This indicates that these two components are critical points requiring immediate repair and maintenance attention. Applying FMEA in this context provides tangible benefits, including helping the company formulate a more targeted maintenance strategy, reducing the risk of recurring damage, and minimizing downtime that impacts production. With more systematic maintenance, operational efficiency can be improved while extending the lifespan of the Ripple Mill machine.

Accurate evaluation of head losses is essential in industrial systems transporting viscous chemical fluids, such as sodium hydroxide (NaOH), to ensure hydraulic efficiency and operational reliability, particularly in chlor alkali plants. This study analyses major and minor flow losses in the NaOH piping system at PT X Chlor Alkali Plant, Porsea, and evaluates the pipe design's hydraulic feasibility. After defining system parameters—including fluid properties, pipe geometry, and the number and type of fittings—technical calculations were conducted to assess flow profiles and pressure losses along two main pipe routes. A quantitative analysis using the Moody diagram and operational data reveals that minor losses dominate, contributing over 75% of total head loss in both routes. The total head loss remains within the pump's rated capacity (18 m), though with a narrow margin. A pipe diameter of 0.114 m produces a flow velocity of 0.79 m/s, aligning with recommended industrial standards for corrosive fluids. The use of Sch.80 stainless steel proves effective in minimizing frictional losses, particularly under turbulent flow conditions. These findings highlight the critical role of fitting configurations and material selection in optimizing chemical process piping systems.

Indonesia, as the world's largest archipelagic nation, holds a strategic position while simultaneously facing significant challenges in maintaining the sovereignty and security of its maritime territory. Increasingly complex maritime threats, such as illegal fishing, smuggling, and potential geopolitical conflicts, demand a transformation in maritime defense strategies to be more efficient and sustainable. In an era of increasing global awareness of the climate crisis, the maritime sector, including the defense sector, is being encouraged to decarbonize through the implementation of environmentally friendly ship technology. This research uses a literature review approach by examining various findings related to sustainable propulsion technology innovations relevant to the development of Indonesia's maritime defense fleet. The study results show that a hydrogen- and battery-based hybrid propulsion system can reduce carbon emissions by up to 73% and increase energy efficiency by 35%. In addition, wind-assisted propulsion sistem (WAPS) technology such as Flettner rotors and wing-sails contributes significantly to reducing fuel consumption by up to 30%, while extending ship cruising range without the need for intensive refueling. Meanwhile, the application of Computational Fluid Dynamics (CFD)-based propeller design optimization has been proven to reduce energy consumption by 13.2% and reduce noise levels by up to 15 dB, which greatly supports the needs of stealth operations in military missions. This study concludes that the implementation of environmentally friendly ship technology not only provides benefits in terms of energy efficiency and emission reduction, but also strengthens the operational resilience and strategic competitiveness of the Indonesian naval fleet amidst the dynamics of global maritime security. Thus, the Green Navy concept can be seen as a relevant and urgently needed sustainable defense strategy.

This research focuses on the development and evaluation of an Adaptive Edge-AI framework designed to optimize real-time data processing and decision-making in resource-constrained environments, specifically within smart city infrastructures. The primary problem addressed is the challenge of minimizing latency, reducing energy consumption, and ensuring the reliability of Cyber-Physical Systems (CPS) when using Internet of Things (IoT) devices. The objective of the study is to assess the effectiveness of this framework in real-world smart city applications such as traffic monitoring, environmental sensing, and smart utilities management. The proposed method integrates lightweight AI models, edge computing, and adaptive resource management techniques, including Federated Learning and Neural Architecture Search, to ensure optimal performance while addressing hardware constraints. The main findings reveal that the framework significantly improves real-time inference speed, reduces energy consumption of IoT devices, and enhances CPS reliability by minimizing communication delays and ensuring continuous system operation despite network disruptions. The application of this framework to smart transportation and urban utilities further demonstrates its potential to optimize city management processes. The study concludes that the Adaptive Edge-AI framework offers a promising solution for smart cities, enhancing operational efficiency, sustainability, and resilience. It is recommended for integration into smart city infrastructures to enable better resource management and decision-making in real-time applications.

This article discusses the four-month internship experience at PT Pos Indonesia Regional V Surabaya, specifically in the Finance and Accounting section, with a focus on evaluating the effectiveness of using the SAP S/4HANA system in recording financial transactions. The research used a descriptive qualitative approach with a literature study method that was analyzed thematically. The results showed that SAP supports real-time transaction recording, is integrated between modules, has an adequate audit trail, and increases HR competence in terms of accuracy and work efficiency. The conclusion shows that the SAP system has proven effective in supporting operational efficiency and internal control of the company, while providing practical experience and important learning for students in facing the digital and integrated world of work.

This community service program focuses on transforming financial management at Pharmacare Pharmacy Ciputat through the integration of digital accounting and strengthening human resource (HR) management. The background to this activity stems from the problem of partners who still rely on manual recording for financial transactions, inventory management, and report preparation. This condition results in inefficiency, late reporting, potential recording errors, and difficulties in strategic decision-making. In addition, limited HR competency in the use of digital accounting technology and the absence of financial standard operating procedures (SOPs) are major obstacles to improving organizational performance. The main objective of this activity is to implement an integrated digital accounting system capable of producing real-time financial reports, increasing inventory management efficiency, and building transparent financial governance. Simultaneously, employee competency is improved through intensive training and mentoring in the use of accounting software and the preparation of financial SOPs. The involvement of students and faculty in this activity aligns with the spirit of Independent Learning and Independent Campus (MBKM) and supports the achievement of the university's Key Performance Indicators (IKU), particularly in providing off-campus experiences and utilizing work results for the community. Through this program, it is hoped that Pharmacare Ciputat Pharmacy can improve operational efficiency, strengthen business sustainability, and provide more optimal healthcare services. More broadly, this activity contributes to community economic empowerment by strengthening the capacity of small businesses in the healthcare sector.

The rapid development of information and communication technology has opened up significant opportunities to enhance service efficiency in various fields, including the beauty industry. Soraaya Studio, which offers a range of beauty services, currently still manages appointment scheduling manually. This manual system leads to several challenges, such as difficulties in efficient schedule management, data duplication, recording errors, and disorganization in the service reservation process. Furthermore, communication with customers regarding schedule confirmation becomes less effective. With the increasing number of customers, this manual scheduling system is no longer able to meet the growing complexity of operational needs.To address these issues, a web-based appointment scheduling system has been designed, which is integrated and user-friendly. This system is built using the PHP programming language with a MySQL database and features a responsive interface, making it easily accessible from various devices, including desktops and mobiles. Key functionalities provided include real-time creation, modification, and cancellation of appointments, management of service availability, and automated notifications via email or text messages to customers and studio staff. The implementation of this system aims to improve the accuracy and speed of the scheduling process, reduce manual errors, and facilitate schedule monitoring by management and staff, thereby enabling Soraaya Studio to provide a more professional and satisfying service to its customers.

PT Udara jadi Bersih Bekasi is a company engaged in testing Heating, Ventilation, and Air Conditioning (HVAC) systems. So far, the process of recording test results is still carried out manually using paper media. This process poses a number of obstacles, such as delays in recording, potential input errors, and limitations in accuracy and data storage. This condition also has an impact on delays in the submission of test results information to supervisors, who should need fast and accurate data for decision-making. To answer this problem, a web-based application is needed to design a web-based application that is able to digitize the entire workflow of recording and reporting HVAC test results. With a web-based system, data can be managed centrally, more structured, and easily accessible at any time. This application is also equipped with QR Code technology to speed up access to test results. Supervisors and technicians only need to scan the code for complete information, so they no longer rely on manual searches that are time-consuming and prone to serious errors in technical documentation. The design of this application uses the Waterfall method which consists of the stages of needs analysis, system design, implementation, testing, and maintenance. UML is used as a tool to describe business processes and system activity flows in detail, so that development can be carried out more systematically, efficiently, and in a targeted manner according to applicable software engineering standards. With the implementation of this application, PT Udara jadi Bersih Bekasi is expected to be able to improve operational efficiency, reduce recording errors, and speed up the information distribution process. In the end, this digitalization will support companies in providing services that are more professional, accurate, innovative, reliable, and according to the needs of the modern HVAC industry in the era of global digitalization.

The rapid growth of RT/RW Net-based internet services among the community has driven the need for an integrated, efficient, and easy-to-use billing system. The self-help RT/RW Net model often faces challenges in terms of administrative management, especially related to customer recording, billing, and financial reporting which are still done manually. Common problems faced by partners are payment systems that have not been digitized and minimal transparency in data collection and tracking of customer transactions. The purpose of this activity is to design and implement a web-based billing application built using the Laravel framework. This application is designed to facilitate the process of managing customer bills, monitoring internet service usage, and preparing financial reports automatically and in a structured manner. The method of implementing the activity includes the system design stage, training partners in using the application, and assistance in direct implementation in the RT/RW Net operational environment. The results of the activity show that the developed system has succeeded in automating most of the billing process and increasing the efficiency of administrative management by up to 80%. In addition, this system also has a positive impact on increasing transparency and accuracy of customer data. Suggestions for further development include the addition of automatic payment features through integration with payment gateways, as well as improving the user interface to make it more responsive and user-friendly.

The laundry business is rapidly growing in urban society, especially in areas with a high activity rate. One of the main challenges is the manual transaction recording process, which causes inefficiency and potential errors. This research aims to design and develop a web-based cashier system for Laundry Indimo Azza using the Prototype method. The system is designed to support customer data recording, automatic service fee calculation, service and employee management, and structured transaction and financial reporting. The Prototype method was chosen due to its ability to adapt to user needs through design and evaluation iterations. Testing results using white box and black box methods show that the system works according to expectations, increasing operational efficiency and speeding up customer service.

This paper investigates how Big Data Analytics (BDA) can accelerate the transition to a low-carbon digital economy. We present a systematic literature-based research framework (2015–2025) that synthesizes applications of BDA in energy systems, transportation, industry and supply chains. The methodology combines systematic review and conceptual modelling to identify pathways through which BDA reduces emissions: (1) demand-side optimization, (2) operational efficiency, (3) predictive maintenance and (4) data-driven policy and market instruments. Results highlight concrete case examples smart grids, digital twins, and green supply-chain analytics and quantify benefits reported in recent literature. Key challenges such as data governance, carbon costs of computing, and policy integration are discussed. The paper concludes with policy recommendations and a research agenda to align digitalization with decarbonization goals.

This study aims to analyze the effect of leverage, liquidity, and company size on profitability in food and beverage companies listed on the Indonesia Stock Exchange (IDX) during the 2019–2023 period. Testing was conducted both partially and simultaneously to obtain a comprehensive picture of the relationship between variables. This study uses a quantitative approach with a sample of 14 companies selected through a purposive sampling method based on certain criteria, such as the completeness of annual financial reports during the study period and the availability of relevant data. The data used are secondary data obtained from the official IDX website (www.idx.co.id), including annual financial reports containing information on total assets, total liabilities, total equity, financial ratios, and the company's profit level. Data analysis was carried out using the multiple linear regression method using SPSS version 26 software, so that the effect of each independent variable on the dependent variable can be tested both individually and together. The results of the study indicate that simultaneously, the variables leverage (X1), liquidity (X2), and company size (X3) have a significant effect on profitability (Y). However, partial test results revealed that leverage had a negative and significant effect on profitability, indicating that a high proportion of debt can reduce a company's ability to generate profits. Meanwhile, liquidity and company size were not shown to have a significant influence on profitability, suggesting that these factors are not the main determinants of profit performance in this sector. This study implies that food and beverage company management needs to carefully consider capital structure to maintain profitability. For further research, it is recommended to add other variables such as operational efficiency, sales growth, and dividend policy, as well as extend the observation period for more in-depth and representative analysis results.