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The conversion of agricultural land to non-agricultural land continues to increase along with the pressures of urbanization, industrialization, and settlement expansion. This condition poses risks to food security, environmental sustainability, and farmer welfare. This article reviews literature based on 25 abstracts/research results on LP2B in Indonesia to map policy implementation patterns, the relationship between LP2B and regional spatial planning, inhibiting factors, and the direction of policy strengthening. The method used is a narrative review with thematic synthesis of normative legal studies, juridical-empirical, qualitative, mixed methods, and spatial-quantitative approaches. The results of the review indicate: (1) LP2B is highly dependent on the harmonization of spatial planning policies, especially RTRW/RDTR and licensing mechanisms based on KKPR-OSS; (2) many regions are still stuck at the land inventory-identification stage, not yet reaching the determination and operational protection through LP2B Regional Regulations; (3) dominant obstacles include regulatory asynchronous, weak law enforcement, minimal cross-agency coordination, limited data by name by address, suboptimal socialization, and conflicts of interest in non-agricultural development; (4) incentive-disincentive instruments have not been implemented consistently, although socially farmers tend to accept LP2B protection; and (5) quantitative evidence at the national level shows that LP2B policies have a positive effect on the percentage of rice fields, despite being suppressed by population density and real estate sector growth. This article emphasizes the need for an integrated spatial governance approach, strengthening regional institutions, and designing policies that are socially and environmentally just to ensure that LP2B is effective in maintaining regional food security.

The success of information systems projects in the digital transformation era is often hindered by unhealthy team dynamics, even when technical aspects have been optimally met. This study aims to analyze the synergy between inclusive communication strategies and digital leadership styles in building team health and sustainable performance. The research method employed is a qualitative literature study, integrating variables such as digital leadership, psychological safety, and knowledge management. The results indicate that digital leadership serves as a primary catalyst in creating a psychologically safe work environment, which in turn enhances the creative self-efficacy of team members. Synergy is effectively established when leaders adopt transparent communication channels through digital collaboration tools to mitigate role conflict and technostress within hybrid work environments. Furthermore, knowledge coordination is proven to strengthen team cohesiveness through the conversion of personal knowledge into strategic organizational assets. The study concludes that the integration of empathic communication and adaptive leadership is the fundamental basis for the cognitive, psychological, and operational health of the team. This research produces a managerial synergy framework to mitigate the risk of project failure caused by human factors in the digital era.

This study investigates the effectiveness of digital transformation in enhancing client acquisition, using a case study of a lamp business in Indonesia. Established in 2021, the company initially operated through traditional offline channels but expanded to online platforms in 2022, integrating digital tools including AI-based financial management systems to streamline operations and support decision-making. The research focuses on comparing offline and online strategies, examining key performance indicators such as revenue contribution, customer acquisition costs, conversion rates, and operational challenges encountered in both modes. In addition, the study explores whether the observed revenue growth following digitalization is primarily driven by online sales or whether it benefits from a hybrid approach that combines both online and offline channels. By analyzing these aspects, the study seeks to provide insights into the practical implications of digital transformation for small and medium-sized enterprises (SMEs), particularly in the Indonesian market. The findings are expected to clarify whether adopting digital strategies offers a measurable advantage over traditional methods in terms of efficiency, cost-effectiveness, and market reach. Ultimately, this research aims to inform SME owners and managers about best practices for leveraging digital tools to enhance client acquisition and drive sustainable business growth.

This research aims to develop and evaluate the performance of a steam plant prototype designed as an alternative source of electrical energy to support the Vessel to Grid (V2G) concept. Utilization of backup energy on ships is becoming important as electricity demand increases and demands for a more sustainable electrical system. This system relies on ESP32 microcontroller technology as a control center that functions to monitor and control several key parameters, including steam pressure, combustion temperature, boiler water level, and the generated electrical voltage. The research method used is an experiment with a static and dynamic testing approach. Static testing is carried out to measure the performance of main components such as the boiler, turbine, and generator separately, while dynamic testing focuses on evaluating the overall system by involving the integration of sensors and supporting actuators. The test data is then analyzed quantitatively to determine the system's response to variations in steam pressure, temperature, and other operational conditions. The results show that the steam produced by the boiler is able to rotate the turbine, thereby driving the generator to produce electricity. The maximum voltage achieved is 25.7 volts at a steam pressure of 50 psi. The highest energy conversion efficiency was recorded at 4%, while the lowest efficiency was 0.9%. These findings demonstrate that, despite its relatively low efficiency, the prototype can function as an alternative energy source and emergency backup solution. Thus, this research provides an initial contribution to supporting the implementation of the V2G concept through the development of a small-scale steam plant-based energy conversion system.

Distribution is an important aspect that affects the operational efficiency of a company, especially in terms of goods delivery. This study aims to develop an optimization model for LPG gas distribution routes using Excel Solver based on geographic coordinate conversion. In this study, the method used includes converting geographic coordinates from decimal to Degree-Minute-Second (DMS) format, followed by conversion to kilometers to form a more accurate distance matrix. The optimization model was built using the Capacitated Vehicle Routing Problem (CVRP) approach, which takes into account vehicle capacity constraints (a maximum of 560 cylinders per truck) and the limited number of available fleets, which is only one truck. The results show that coordinate conversion produces high accuracy in calculating distances between distribution locations. By using Excel Solver, the optimization solution successfully minimizes the total distance traveled compared to the conventional route, where distribution is carried out more evenly to 57 scattered LPG base locations. The addition of Solver Parameters Evolutionary and All Different constraints proved effective in avoiding duplication of visits and producing optimal distribution routes. This solution not only improves distribution time and cost efficiency, but also improves service to customers by reducing delivery delays. The success of this optimization model is expected to be implemented by other distribution companies to improve their operational performance. This study also highlights the importance of selecting the right software to aid the distribution optimization process. Excel Solver, despite its simplicity, proved highly effective in solving complex distribution routing problems, especially when combined with coordinate conversion techniques that yield more accurate distances. Furthermore, the application of the CVRP method enabled more efficient decision-making in determining distribution routes, taking into account vehicle capacity and fleet limitations.

Measuring Liquefied Petroleum Gas (LPG) levels and inventory in storage tanks is a critical aspect of terminal operations, directly influencing safety, operational efficiency, and accurate stock management. The Integrated Terminal Palembang – Pulau Layang LPG Site has implemented a servo-type Automatic Tank Gauging (ATG) system, namely the Proservo NMS81, to provide precise and real-time volume measurements. Despite its operational importance, there remains a limited in-depth understanding of how this ATG system functions, particularly regarding the complete process from sensing LPG levels to converting them into accurate inventory data. This study aims to analyze the working mechanism of the Proservo NMS81 in measuring LPG height and generating digital stock data for monitoring purposes. The research method combines a literature review of the Proservo NMS81 technical datasheet and related scientific references with direct field observation (KSM-LP) at the LPG Pulau Layang site. The analysis covers the operating principle of the servo sensor, which relies on displacement measurement via a mechanical float and wire system; the analog-to-digital conversion process utilizing a 12-bit ADC to transform continuous signals into discrete digital values; the communication protocols employed, including HART and Modbus RS-485, for transmitting processed data to the control system; and the algorithmic data processing that converts tank level measurements into standardized inventory figures based on tank calibration tables and product density. The results of this study are expected to improve technical knowledge regarding servo-type ATG systems, enhance the accuracy and reliability of inventory monitoring, and contribute to more informed operational decision-making. Furthermore, the research findings are intended to serve as a valuable academic reference for the application of advanced instrumentation technology in the energy industry, supporting both professional practice and further scholarly exploration in the field.

The low proportion of Grade A harvest quality in Hokkaido corn farming remains a challenge for horticultural agribusiness practitioners. This study aims to develop an operational strategy based on a managerial evaluation of key production factors to improve technical efficiency and harvest quality. The research was conducted at PT Agricole Indonesia Makmur, Cianjur, using data from 24 planting periods in 2024. Six production input variables were analyzed to identify the most influential factors on yield quantity and quality. The results show that only three variables watering frequency, organic fertilizer, and plant age at harvest consistently contributed significantly to the production of Grade A output. Although these variables are inelastic, they play a critical role in maintaining quality. The proposed strategy includes a 10% increase in harvest quantity and a 30% conversion from Grade B to Grade A. Simulation results indicate an additional 7.67 kg of Grade A yield per planting period, generating a value increase of IDR 239,490. The strategy is considered feasible with a positive Return on Investment (ROI) of 14.04% assuming a Grade A selling price of IDR 35,000/kg.

Interpretation of debt-to-equity swap provisions for goods purchase transactions as stipulated in the Financial Services Authority Regulation (POJK) Number 14/POJK.04/2019 concerning Affiliated Transactions and Conflicts of Interest in Certain Transactions. The principle of openness and fairness in transactions between affiliated parties, including in the context of debt-to-equity swaps. However, this provision does not explicitly regulate the conversion of debt arising from goods purchase transactions, thus creating room for legal interpretation regarding whether business debt from operational activities can be converted into equity participation through the issuance of new shares. This study aims to analyze the implementation of debt-to-equity conversion as a financial restructuring strategy, with a focus on legal certainty and protection of public shareholders based on POJK 14/2019. The study uses a normative legal approach with the method of statutory regulations and case studies on PT SLJ Global Tbk. The results of the study indicate that PT SLJ Global Tbk has complied with the formal procedures of POJK 14/2019, including information disclosure, GMS approval, and unaffiliated creditor criteria. However, the conversion of business debt creates legal ambiguity due to the lack of clarity as to whether the debt meets the definition of “loan” in POJK 14/2019. In addition, the dilution of public shares by 34.32% without adequate protection mechanisms indicates a lack of legal certainty. The study recommends normative interpretation and strengthening of regulations to ensure fairness and legal certainty in the practice of debt conversion. Keywords: ; ; ; ; 

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.

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

The transport industry stands out as a crucial domain in bolstering Indonesia's journey toward economic revitalization, swift progress, and equitable distribution. At present, Indonesia is in the process of establishing a high-speed railway sector that adheres to global benchmarks. Rail-based transit systems exert considerable influence on the mobility of both individuals and commodities. Trains possess the capacity to convey substantial volumes of commuters and freight in one journey, thereby playing a role in diminishing operational expenses for transportation fleets. Braking is an important aspect of driving because it affects safety, vehicle control, and vehicle efficiency. In order to develop braking research, high-speed train braking test equipment is needed to describe the actual conditions during braking. High-speed trains are a type of train capable of traveling at speeds above 200 km/h. The braking applied to these high-speed trains involves several combined forces, including regenerative braking and pneumatic braking. In regenerative braking, deceleration occurs due to the conversion of kinetic energy into electrical power. This mechanism is carried out when the train is at an operational speed of 220 km/h until it decelerates to 160 km/h. Next, pneumatic braking was applied at a speed of 160 km/h until the train slowed down and came to a stop. This study shows how the calculation process was carried out using a scale of 1:4 at a speed of 160 km/h.

In the rapidly developing digital era, online businesses face increasing challenges to achieve significant profits without sacrificing spending efficiency. To overcome this challenge, an optimal online marketing strategy is needed that can reach the right target market without significantly increasing operational costs. This journal discusses several online marketing strategies that are effective in increasing profits relevant to expenditure. From a deep understanding of the target market to the use of social media and careful data analysis, every step taken is based on the principles of efficiency and effectiveness. By implementing the right marketing strategies, businesses can increase their visibility online, attract more potential customers, and increase sales conversions without having to exceed their available budget. Thus, this journal provides practical guidance for business owners and marketers to achieve success in their online sales without sacrificing profitability.

In the rapidly developing digital era, online businesses face increasing challenges to achieve significant profits without sacrificing spending efficiency. To overcome this challenge, an optimal online marketing strategy is needed that can reach the right target market without significantly increasing operational costs. This journal discusses several online marketing strategies that are effective in increasing profits relevant to expenditure. From a deep understanding of the target market to the use of social media and careful data analysis, every step taken is based on the principles of efficiency and effectiveness. By implementing the right marketing strategies, businesses can increase their visibility online, attract more potential customers, and increase sales conversions without having to exceed their available budget. Thus, this journal provides practical guidance for business owners and marketers to achieve success in their online sales without sacrificing profitability.

This study aimed to evaluate the effect of three feeding methods-manual, automatic, and sensor-based-on the growth and feed efficiency of White Snapper (Lates calcarifer). The research was conducted from April to July 2024 in fish farming ponds in North Nias. The research method used was a field experiment with a complete randomized design (CRD) which was analyzed using ANOVA test to compare the significant effects of each feeding method. The results showed that the sensor-based feeding method produced the highest average fish weight growth (3.85 g/day) with the best feed conversion efficiency (FCR) (1.25), significantly superior to the manual and automatic methods (p < 0.05). The sensor-based method proved to be more efficient in meeting fish feed requirements precisely, improving feed efficiency and reducing operational costs. Based on these results, the use of sensor-based technology in the feeding system is recommended as an innovative solution to improve the productivity and sustainability of White Snapper aquaculture.

Layout is one of the strategic operational decisions that also determines the efficiency of the company's operations in the long term. The right layout shows the characteristics of the adjustment of the layout of the operational facilities with the products or types of services produced and their conversion processes. A good layout will contribute to increasing the company's productivity. CV. ESA is a furniture company that produces multi-products with a make-to-order production system. The layout of the production department at CV. ESA has problems in terms of the distance of moving the cutting results to the installation of the frame which is less efficient. The purpose of the study is to find out and redesign a good production facility layout so that it can minimize the distance and cost of material handling at CV. ESA Banyuwangi. The results of the redesign of the production facility layout concluded that the effective and efficient arrangement of the department layout is in the sequence B C I J K M N O. From the results of data processing, it was obtained about the redesign of the production facility layout in order to obtain a comfortable work area and to minimize the distance of material movement with a total distance of movement per day of 2,516 smaller than the initial layout of 4,916. Calculation of optimum material transfer costs for the initial layout Material transfer costs per month = Rp 23,990 while in the proposed layout Material transfer costs per month = Rp 12,239.

Komoditas unggulan pada sektor perkebunan di Desa Tambu adalah kelapa. Produksi minyak kelapa sudah lama terhenti karena rantai produksi yang sangat panjang. Melihat potensi dan permasalahan tersebut, Kegiatan ini bertujuan untuk dapat mengaktifkan kembali kegiatan inbound logistics dan operasi konversi pembuatan minyak kelapa di Desa Tambu serta membangun semangat masyarakat setempat untuk memanfaatkan potensi produk desa yang dapat meningkatkan taraf ekonomi masyarakat. Metode yang diterapkan adalah memberikan pendampingan langsung berupa praktek pengolahan kelapa menjadi minyak kelapa melalui tahapan yang sistematis sehingga masyarakat dapat meningkatkan pengetahuan dan keterampilannya dalam pengolahan minyak kelapa yang terstandar. Dengan adanya kegiatan tersebut masyarakat mulai memproduksi kembali produk unggulan Desa Tambu yaitu minyak kelapa desa. Akhirnya mereka mengetahui bahwa rantai produksi yang panjang juga akan menghasilkan produk yang berkualitas dan dapat meningkatkan perekonomian masyarakat.