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The use of Village Funds does not always go according to plan and optimally. Tanjungsari Village has become one of the villages with the largest Village Fund income in the last two years. This research aims to look at the optimization of the use of Village Funds carried out by the Tanjungsari Village government as a manifestation of the implementation of Law number 6 of 2014 concerning Villages. The research method used in this research is descriptive analysis method with a qualitative approach. The results of this research are divided into three, the first is that the Village Fund has been utilized by Tanjungsari Village for village development and community empowerment in accordance with the priorities for utilizing Village Funds based on directions from the central government. Second, the use of Village Funds in Tanjungsari Village has provided many benefits for the people of Tanjungsari Village which are in accordance with the objectives of the Village Fund. Third, the use of Village Funds in Tanjungsari Village has not been running optimally because the use of Village Funds is still unable to solve the problem of unemployment and poverty and significantly increase original village income in Tanjungsari Village.

Effective bureaucratic management depends on aligning competencies with job placement. This study examines Echelon 3 and 4 officials in Pasuruan Regency, Indonesia, focusing on the suitability of their educational backgrounds, skills, and job roles. A descriptive quantitative approach was used with 77 respondents, including 23 Echelon 3 and 54 Echelon 4 officials. The findings indicate moderate suitability, with an average score of 3.5 out of 5. While many officials possess advanced educational qualifications, gaps in training adequacy and skill alignment remain. Technology usage is a key strength, reflecting readiness for digital transformation. These results emphasize the need for systematic training and strategic human resource allocation to enhance bureaucratic effectiveness. The study contributes to discussions on workforce optimization in public administration, providing actionable insights for policymakers. Future research should expand on these findings by exploring competency-based interventions and their impact on organizational performance.

This research examines the Android operating system in the context of Augmented Reality (AR) and Virtual Reality (VR) applications with a focus on the Moblo (AR) and Relax (VR) applications. Android, as the primary operating system in mobile devices, offers a powerful and flexible platform for AR and VR application development. Moblo is an AR application that allows users to design and visualize furniture in a real space, while Relax is a VR application that provides meditation and relaxation experiences in a virtual environment. This research aims to understand how the Android operating system supports the development and operationalization of AR and VR applications, as well as evaluating the performance and user experience of these two applications. The results show that Android provides significant support for AR and VR application development, with Moblo and Relax showing good performance and providing a satisfactory user experience. However, further optimization is needed to ensure consistent performance across Android devices.

This study explores the integration of Artificial Intelligence (AI) into smart home systems using the Android operating system to enhance security, privacy, efficiency, and user comfort. Key security measures include data encryption, robust authentication methods, sandboxing, and AI integration, specifically leveraging Google Assistant for improved privacy controls. Maintenance strategies for smart homes emphasize energy management, device condition monitoring, and enhanced safety features. AI adaptation to user habits enhances productivity and situational awareness, while Android's role in connecting various IoT devices facilitates remote control and energy-efficient recommendations. Methods such as Eco Android, Greensource, byte-code transformations, and automated energy diagnosis tools aid in optimizing energy use. The comparison between smart and non-smart homes highlights the efficiency and convenience of smart homes despite higher installation costs and potential network issues. The development and deployment of an Android-based application, SafeHause, exemplifies practical implementation, emphasizing end-to-end testing, security updates, and user education. The findings affirm that AI integration with Android significantly improves the smart home experience by enhancing energy optimization, data security, and personalized user interaction. Furthermore, the study discusses future trends in smart home technology, such as the potential for more advanced AI algorithms and machine learning techniques to provide even greater personalization and automation. The importance of regular software updates and the role of user feedback in refining smart home systems are also highlighted, ensuring that these technologies continue to evolve and meet user needs effectively.  

In the growing digital era, the use of TikTok by local Micro, Small, and Medium Enterprises has become a significant concern in an effort to expand markets and increase sales. This article analyzes the challenges and strategies that can be adopted by  in facing e-commerce dynamics and utilizing the TikTok Platform as E-Commerce effectively. The research method used is using a qualitative approach method by conducting literature studies and literature studies. The method for data collection is obtained from the official website (e-commerce usage data) and studying theories from various literatures related to the research. The results show the importance of efficient advertising budget management, optimization of logistics and delivery, improved skills in content creation, strategic collaboration, and campaign performance monitoring as key steps in facing challenges and taking advantage of opportunities in TikTok Commerce. Through a deep understanding of market dynamics and the implementation of appropriate strategies, MSMEs can strengthen their presence in TikTok Commerce and increase their competitiveness in the competitive e-commerce ecosystem. Translated with DeepL.com (free version)

The potential for open military conflict in various parts of the world is still very possible to fulfill various national interests possible to fulfill their respective national interests. Since the past, Indonesia has been the charm of various nations because of its abundant natural resources. As the largest archipelago bordering a number of neighboring countries, the unresolved boundaries of a number of state territories are also one of the potential conflicts. The development of naval forces by a number of regional countries bordering Indonesia must be examined with efforts to the development of the strength of the Indonesian Navy in addition to creating a deterrence effect/deterrence effect as well as to protect and uphold sovereignty and secure Indonesia's national interests. secure Indonesia's national interests. KRI type PKR 105 is currently the the mainstay of the Indonesian Navy's power with a number of capabilities in naval warfare. but the author suggests that there needs to be optimization to improve anti-submarine warfare (ASW) capabilities.    

The function of the Navy can be understood as a trinity, namely the idea of three-in-one reflected in the roles of military, diplomacy and polisinil. The implementation can be through the Cadet Exchange program which carries out the exchange of Cadets from friendly countries to AAL and from AAL to friendly countries with a certain period of time. The main purpose of this research is to determine the strategy so that the Cadet Exchange program can run optimally. This research was conducted by collecting respondents using a questionnaire with purposive sampling technique. The results of the study indicate that the Cadet Exchange program strategy is in quadrant 1, namely by implementing an aggressive strategy. With several strategies, namely good academic and foreign language skills of AAL cadets are maintained and improved in supporting the Cadet Exchange program, the Cadet Exchange program at AAL can support the realization of AAL as a World Class Naval Academy, good attention and communication between AAL institutions and cadets can help and facilitate the implementation of the Cadet Exchange program, and the development of communication technology through online (zoom meeting or google meet) can improve the Cadet Exchange program.    

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in Indonesia's economy but often face challenges in marketing their products, especially in the digital era. This study aims to design and evaluate the effectiveness of digital marketing training for MSME activists in Sangatta District, East Kalimantan. The research methodology uses a mixed-methods approach with 50 MSME actors as subjects. The training conducted includes the basics of digital marketing, the use of social media, content creation, search engine optimization (SEO), and data analysis.The results show a significant increase in participants' knowledge and skills in digital marketing. Additionally, the training successfully increased sales and product visibility of MSMEs. Training participants began adopting digital marketing strategies and using data analytics for more effective decision-making. These positive impacts indicate that digital marketing training can be an effective solution to enhance the competitiveness and sustainability of MSME businesses. This study recommends the implementation of advanced training and continuous support for MSME actors, as well as collaboration between the government, universities, and the private sector to provide necessary resources. Thus, MSMEs in other regions are expected to benefit from similar programs to face challenges in the digital era.

This work introduces a novel hybrid conjugate gradient (CG) technique for tackling unconstrained optimisation problems with improved efficiency and effectiveness. The parameter  is computed as a convex combination of the standard conjugate gradient techniques using  and . Our proposed method has shown that when using the strong Wolfe-line-search(SWC) under specific conditions, it achieves global theoretical convergence. In addition, the new hybrid CG approach has the ability to generate a search direction that moves downward with each iteration. The quantitative findings obtained by applying the recommended technique about 30 functions with varying dimensions clearly illustrate its effectiveness and potential.    

This abstract discusses an effective approach in creating a landing page for the Banggi Market Mangrove Bridge Tour. The proposed method includes analysis and planning, user-friendly design, content development, interactive features, testing and optimization, as well as launch and promotion. Alternative methods include user experience-based, dynamic content, data-driven, collaborative, and technology-based marketing approaches. The results show that by prioritizing user needs, optimizing content, and utilizing interactive features and effective promotions, landing pages can increase visits and awareness of environmental conservation. Data analysis and user feedback are important for continuous improvement. A user experience-driven approach ensures easy navigation and relevant information, while dynamic content and data-driven marketing enable strategy adjustments. Collaboration and advanced technology are also important. Further data collection is needed to increase the effectiveness of landing pages as promotional and environmental education tools.

This study analyzes the "NYC TLC Trip Record" dataset for the period January 1, 2023 to January 31, 2023 to understand taxi usage patterns in New York City. The objectives to be achieved in this analysis include: (1) Identify the days and times with the highest demand for taxi services, (2) Identify the boroughs with the highest demand for taxi services. We applied univariate analysis for this analysis. The results show that the day with the highest demand occurs on Tuesday for the densest time occurs in the vulnerable time of 3 pm to 6 pm. The boroughs with the highest taxi demand are Manhattan, Queens, and Brooklyn. This analysis provides the results for NYC TLC to develop a data-driven optimization strategy. This analysis not only helps in identifying demand hotspots but also provides insights for more efficient taxi scheduling and placement. With this analysis, it is expected that more effective pick-up time and location optimization strategies can be developed, thereby improving operational efficiency and customer satisfaction in taxi services in New York City.

Free trade practices are formed based on agreements, which are binding on the parties and must be implemented in good faith. KPBPB Sabang is an area within the jurisdiction of the Republic of Indonesia which is separate from the customs area so that it is free from import duties, value added tax, sales tax on luxury goods, and excise (fiscal and non-fiscal incentives). KPBPB Sabang has the potential to become a shore base port to support the oil and gas (oil and gas) industry off the coast of Aceh, and oil and gas exploration activities in the Andaman (Sea) Block. Through SWOT analysis, the Sabang area has great potential to become a connectivity hub because it has met the minimum requirements. However, the synergy between regulations, facilities and services at KPBPB Sabang still needs to be improved, both as a multi-purpose port and as a shore base port.

This community service was carried out in Sumbersari Hamlet, Community Service Activities were carried out in Mojowatesrejo Village, Kemlagi District, Mojokerto Regency with the target of understanding Digital Marketing Optimization and the Legality of Micro, Small and Medium Enterprises Development (U.M.K.M). Carrying out community service, the main aim of this activity is to increase insight and knowledge regarding Optimization of Digital Marketing and the Legality of Micro, Small and Medium Enterprises (UMKM) Development in Mojowono Village. In order to obtain and support a conducive working atmosphere, work together to build productive partnerships. Therefore, the socialization carried out in Mojowono Village, Kemlagi District, Mojokerto Regency is very important to carry out. Other objectives include providing an understanding of technological advances that must be utilized properly so that they can increase income in society. This business activity must of course be maximized and must be equipped with a business permit so that it can provide certainty and legal protection for Micro, Small and Medium Enterprises(UMKM)

Education is an important activity for every person to be able to develop the potential that exists within him. Currently, the curriculum applied to education in Indonesia uses the Merdeka Belajar curriculum. The Merdeka Belajar curriculum has a system where teachers and students can of course have the freedom to learn independently, be creative and innovate. In the Merdeka Belajar curriculum, of course, there are subjects studied by students, one of these subjects is PPKn. The aim of this research is to determine the optimization of the character of elementary school students in PPKn learning based on the Merdeka Belajar curriculum. The type of research used is quantitative, the data collection procedure begins with determining the sample using test techniques, questionnaires, observation rubrics, documentation, as well as the research population and sample, namely class IV students at SDN Balas Klumprik 1 Surabaya. The results of the research show that the Merdeka Belajar curriculum in PPKn learning has an influence in optimizing the character formation of elementary school students. In the conclusion of the research, the influence of the Merdeka Belajar curriculum on PPKn learning as optimizing student character formation in elementary schools is that students are able to optimize character formation in PPKn subjects based on the Strengthening Pancasila Student Profile Project (P5) with the dimension of working together and doing it in life. real.  

This article examines a potential solution to the well-known Travelling Salesman Problem (TSP), which is classified as an NP-hard problem. We also provide a theoretical synopsis of several approaches that have been employed to tackle this problem. A prominent example of a combinatorial problem is the traveling salesman problem (TSP). To address the fundamental PSO algorithm's premature convergence issue and stagnation behavior on TSP, a scout characteristic-based PSO algorithm is suggested.We address Particle Swarm Optimization (PSO), a member of the evolutionary methods class, and outline the methodology for applying PSO to the TSP. Among population-based metaheuristic optimization methods, Particle Swarm Optimization (PSO) is one of the most widely used. Scientific domains such as engineering, chemistry, medicine, advanced physics, and humanities have all effectively employed PSO. Numerous theoretical and empirical results on the convergence and parameterization of PSO versions have been produced as a result of the method's extensive investigation since its introduction in 1995. Hundreds of PSO versions have been developed. It is well recognized that population size has a significant impact on the effectiveness of metaheuristics; nevertheless, no comprehensive research has been done on the appropriate selection of PSO swarm size to date.Through the application of this approach, we examine the effects of various control settings. The ideal solution and the quality of the solution are contrasted.    

Abstract :The financial performance of PT Semen Baturaja (Persero) for the period 2020-2022 needs to be evaluated to determine the effectiveness of management in managing the company's finances. The purpose of the study is to measure the financial performance of PT Semen Baturaja (Persero) through financial statement analysis over the period 2020, 2021, and 2022. This study uses various types of financial ratios such as Liquidity, Solvency, and Profitability. The research method used is qualitative with a quantitative approach. The data used is sourced from the financial statements of PT Semen Baturaja (Persero) Tbk for the years 2020, 2021, and 2022, obtained from the Indonesia Stock Exchange. The analysis results show that the company has good liquidity because current assets are higher than current liabilities. The solvency ratio level is quite healthy. Although the Debt to Asset Ratio (DAR) indicates high debt, the low Debt to Equity Ratio (DER) values show that most of the assets are still funded by equity. The company's profitability level is less healthy. Although the Gross Profit Margin (GPM) shows positive results and is higher than the industry average, other ratios such as Operating Profit Margin (OPM), Net Profit Margin (NPM), Return on Assets (ROA), and Return on Equity (ROE) indicate that the company has significant room for improvement in operational efficiency, cost management, and optimization of asset and equity utilization. Keywords: Analysis, Liquidity, Solvency, Profitability

PT Sayuran Pagi is a company that operates in the agricultural sector and focuses on hydroponic vegetables such as spinach, kale, curly kale and other types of vegetables, and is located in the city of Depok and is a Limited Liability Company (PT). The Morning Vegetable Company has three gardens which are used, one of which is the Cipaku area, Bogor, where all of its production will be sent first to a warehouse in Depok and then distributed to several partners who have collaborated. The increase in consumption of green spinach among the public affects the distribution of this vegetable, which means companies must be able to meet demand with proper distribution. In this research, to determine the shortest route when distributing from the garden to the warehouse using the Dijkstra algorithm. Based on the calculation results, the optimal solution for the shortest route is route A-C-B-F-H-I or from the toll road with a total distance of 10.55km. However, because the focus of this research is on costs, from the results of the research using the Dijkstra algorithm calculation method, it can be concluded that PT. Sayuran Pagi can take the non-toll route because the costs incurred are less than the toll route.

Law No. 19 of 2013 on the Protection and Empowerment of Farmers aims to improve farmers' welfare through various programs, including fertilizer subsidies. However, the distribution of subsidized fertilizers often faces issues such as misallocation, delays, and misuse. The Farmer Card (Kartu Tani), an innovation to facilitate the distribution of subsidized fertilizers, has significant potential to address these problems. This study aims to evaluate the effectiveness of the Farmer Card in the distribution of subsidized fertilizers, identify the challenges faced by farmers in its use, and propose solutions for the optimization of the Farmer Card. Using a descriptive qualitative approach through literature review, this study finds that the main challenges include technical issues, lack of socialization, bureaucratic hurdles, and farmers' distrust of new technology. Proposed solutions include enhancing technological infrastructure, providing intensive training for farmers, and simplifying administrative procedures. The study's results indicate that improvements in these aspects can enhance the effectiveness and transparency of subsidized fertilizer distribution through the Farmer Card.

Background: The rapid growth of warehouse automation and autonomous mobile robots has increased the need for adaptive navigation systems capable of operating safely and efficiently in dynamic industrial environments. Classical path planning algorithms such as A* and RRT perform well in structured settings but exhibit limitations when handling moving obstacles and environmental uncertainty. Objective: This study aims to develop and evaluate a reinforcement learning based navigation framework integrated with sensor fusion to improve path efficiency, collision avoidance, and robustness in dynamic warehouse scenarios. Method: An experimental research design was implemented combining high-fidelity simulation and real-world warehouse prototype testing. Deep Q-Network and Proximal Policy Optimization models were developed and trained using multi-sensor inputs from LiDAR, camera, and inertial measurement units. Performance was evaluated using path efficiency, collision rate, computational cost, and robustness metrics, with benchmarking against classical algorithms. Results: The results demonstrate that the Proximal Policy Optimization model achieved the highest path efficiency and lowest collision rate while maintaining stable computational performance under dynamic conditions. Reinforcement learning models significantly outperformed classical planners in adaptability and robustness, confirming their suitability for scalable industrial warehouse automation.

Background: The rapid advancement of Industry 4.0 has accelerated the integration of digital technologies such as the Industrial Internet of Things (IIoT), edge computing, and Digital Twin systems in smart manufacturing environments. However, many existing implementations remain fragmented and heavily dependent on centralized cloud infrastructures, resulting in latency constraints, limited scalability, and suboptimal real-time decision making. Objective: This study aims to develop and validate an integrated edge based Digital Twin optimization framework that combines IIoT sensing, hybrid edge cloud architecture, and reinforcement learning based adaptive control. Methods: The research adopts a multi phase design consisting of framework development, simulation based validation, and industrial pilot implementation. The proposed system integrates real time data acquisition, localized edge processing, Digital Twin synchronization, and intelligent optimization mechanisms to enhance operational efficiency. Results: The findings demonstrate significant performance improvements compared to conventional cloud based systems, including substantial latency reduction, increased production throughput, reduced downtime, and improved energy efficiency. Scalability and robustness testing further confirm that distributed edge intelligence enhances system resilience under increased workloads and network disruptions. These results indicate that integrating edge computing with Digital Twin modeling and reinforcement learning provides a scalable, responsive, and energy efficient solution for next-generation smart factories.