Publication Search

The scarcity of subsidized 3-kilogram LPG in Tanjungpinang City has become a crucial public issue, primarily due to inaccurate distribution. The Puan Molek Card program was designed as an innovative solution to reorganize the LPG subsidy distribution mechanism to make it more manageable and in favor of poor households and eligible MSMEs. An evaluation based on William Dunn's six dimensions showed that in the initial phase, the program's effectiveness and efficiency were quite high, supported by collaborative data collection between local governments, neighborhood associations (RT/RW), and community social institutions. The card also provided convenient access and reduced the potential for hoarding by irresponsible individuals. However, over time, inconsistent card use and weak oversight caused the program's effectiveness to decline. Many residents returned to using ID cards (KTP) as a substitute, opening new opportunities for distribution irregularities. This indicates that the dimensions of accuracy and accountability have not been maintained sustainably. The study also noted that although LPG distribution was relatively smooth, there is a long-term potential for declining public trust if the government does not immediately implement improvements. Therefore, the main recommendations are strengthening the digital-based monitoring system to record LPG subsidy transactions in real time, as well as integrating the Puan Molek Card with population data to prevent misuse. Furthermore, local governments need to intensify public awareness campaigns on the importance of card use and conduct regular field monitoring. Cross-sector collaboration, including with Pertamina, distribution agents, and independent oversight bodies, is also needed to ensure the program returns to its primary objective: ensuring that the 3-kilogram LPG subsidy reaches those entitled to it.

The Printed Circuit Board (PCB) industry increasingly relies on automation and digitalization to improve efficiency and accuracy in production and distribution processes. One common practice is the use of labels containing product information in the form of barcodes or QR codes, which allow automatic data input and reduce the risk of human error compared to manual writing. However, in current practices, these labels are only attached to PCBs after they have been placed inside casings. This creates a significant limitation, as access to the label information requires disassembling the casing whenever product verification, tracking, or troubleshooting is needed. Such a process not only consumes additional time and resources but also increases the risk of damaging the product. To overcome this challenge, this study proposes the development of a traceability system designed to accurately monitor the location, identity, and status of PCBs throughout the distribution process. The system was implemented as a web-based application capable of generating and printing product information labels in the form of barcodes and QR codes. Each label functions as a unique identifier, ensuring that every PCB can be distinctly tracked from production to final product assembly. All data associated with the labels is automatically stored in a centralized database, providing real-time accessibility, simplifying information management, and enabling faster decision-making in the event of quality control issues. System evaluation was carried out through rigorous testing, which showed a 100% success rate in generating, storing, and retrieving product information without errors. The findings indicate that the proposed traceability system is both effective and efficient, and it offers a practical solution for industries seeking to enhance supply chain visibility, improve product accountability, and reduce operational inefficiencies in PCB distribution and lifecycle management.

Integral equations are essential tools in applied mathematics, with wide-ranging applications in fields such as physics, engineering, and finance. However, solving these equations presents significant challenges, particularly when dealing with complex, high-dimensional, or singular problems. Traditional methods, such as manual analytical techniques or direct numerical approaches, often struggle with computational efficiency, especially for large-scale systems, and may not be suitable for handling ill-conditioned problems. This study aims to develop an efficient numerical method for solving integral equations by combining adaptive quadrature techniques with Python-based iterative solvers. The adaptive quadrature method adjusts the step size dynamically based on error estimates, ensuring high accuracy even in the presence of singularities or near-singularities, which are common in many real-world problems. The iterative solver, based on Krylov subspace methods, enhances computational efficiency by reducing memory usage and improving the convergence speed of the solution. By using these techniques together, the proposed method significantly improves the computational time required to solve large-scale and complex systems of integral equations, while maintaining satisfactory accuracy. The results demonstrate that the adaptive quadrature technique, when combined with the Python-based iterative solver, offers a substantial advantage in both speed and precision compared to traditional methods. The proposed method is especially effective in handling complex, high-dimensional systems and ill-conditioned problems, making it a powerful tool for applied mathematics, physics, and engineering applications. In conclusion, this study presents a robust and efficient approach for solving integral equations, with potential for future research in solving non-linear and multi-dimensional integral equations.

In recent years, rapid advancements in digital technology have significantly transformed global healthcare delivery. The COVID-19 pandemic acted as a catalyst, accelerating the integration of information technology into healthcare systems, particularly through the increased adoption of telemedicine. In the field of internal medicine, which often involves long-term care and management of chronic illnesses, telemedicine presents a promising solution to enhance service accessibility, improve care efficiency, and sustain favorable clinical outcomes. This study aims to conduct a narrative review to explore the impact of telemedicine on patient clinical outcomes, healthcare worker workload, and healthcare system efficiency within internal medicine practice. The review is based on an analysis of peer-reviewed literature published between 2020 and 2025, sourced from major databases including PubMed, Scopus, and Web of Science. Article selection was based on relevance to the topics of telemedicine and internal medicine, contextual applicability, and full-text availability. The findings of the review reveal that telemedicine contributes positively by expanding access to care, reducing travel time and logistical barriers for patients, accelerating clinical response times, and decreasing patient congestion in healthcare facilities. These outcomes are particularly beneficial for patients with chronic conditions who require regular monitoring and consistent communication with healthcare providers. However, the implementation of telemedicine also introduces new challenges, including increased administrative responsibilities and digital workload for healthcare professionals. The study underscores the importance of equipping healthcare systems with adequate digital infrastructure, implementing supportive and flexible policies, and providing comprehensive training for healthcare workers. These measures are crucial to ensure the successful and sustainable adoption of telemedicine in internal medicine. Overall, telemedicine holds strong potential to reshape the future of internal medicine, provided that its integration is strategically managed to balance technological advancement with human-centered care.

This research explores the effectiveness of heuristic techniques for solving combinatorial optimization problems, with a particular focus on the Traveling Salesman Problem (TSP). Combinatorial optimization is a critical area of study, especially in fields like computer science, engineering, and economics, where finding optimal solutions from a finite set of possibilities is crucial. However, the NP-hard nature of many combinatorial problems, such as the TSP, makes traditional exact methods like Branch-and-Bound and Dynamic Programming computationally expensive and inefficient for larger problem sizes. The primary objective of this research is to evaluate the performance of heuristic methods, including Simulated Annealing (SA), Genetic Algorithms (GA), and Iterative Computation techniques, such as Tabu Search (TS) and Particle Swarm Optimization (PSO). These methods are tested for their ability to provide approximate solutions efficiently. The findings reveal that while ACO provided the best solution quality, it had the longest runtime. TS was the fastest, though with slightly lower solution quality. SA and GA demonstrated a balance between solution quality and computational efficiency, but their performance heavily depended on parameter tuning. The hybridization of SA and GA showed potential for improving solution quality but introduced additional complexity. The research concludes that heuristic methods, especially when combined, offer viable solutions for large-scale combinatorial optimization problems, though the trade-off between solution quality and computational time must be considered when selecting an algorithm.

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in supporting Indonesia's economy, contributing 61.07% to the national Gross Domestic Product (GDP). However, MSMEs still face various challenges, particularly low productivity due to limited access to technology and production equipment. A clear example is Kedai Ndeso, located in Jiyu Village, Kutorejo District, Mojokerto Regency. This small food business faces inefficiencies in the noodle boiling process, which is still done manually using conventional methods, resulting in limited production capacity and longer service times. Through this community service program, the implementation team aimed to develop and apply an appropriate technology innovation in the form of a multi-strainer noodle boiler to help improve MSME productivity. The method used was a participatory approach, actively involving the Kedai Ndeso owner throughout each stage of the program, which was conducted from July 13 to 24, 2025. The developed noodle boiler measures 35x35x35 cm and is made of food-grade stainless steel. It features six separate strainers, allowing six portions of noodles to be cooked simultaneously in the same amount of time.nTesting results demonstrated that this tool significantly increased production efficiency without compromising the quality of the noodles. It also led to operational cost savings, especially in terms of energy use and labor time. Additionally, training and outreach activities were carried out to ensure effective knowledge transfer to the MSME owner. This appropriate technology innovation has proven to be a practical solution for MSMEs in the culinary sector, helping them increase productivity and competitiveness while maintaining consistent product quality and ensuring food safety. Therefore, this initiative provides a tangible contribution to supporting the sustainability and independence of small enterprises in rural areas, empowering them to compete more effectively in the modern economy.

This study aims to analyze the electrical energy consumption of a bench-type drilling machine, RYU RDB 13, by varying machining parameters in the form of spindle speed and feed rate. Electrical energy is a critical aspect of production efficiency in the manufacturing industry, particularly in machining processes that require continuous power consumption throughout the cutting operation. The material used in this study is aluminum 6061, chosen for its lightweight, corrosion resistance, and wide application in the automotive and aerospace industries. The drilling process was carried out using three spindle speed variations: 620 rpm, 920 rpm, and 1280 rpm, along with three feed rate variations: 0.04 mm/rev, 0.08 mm/rev, and 0.1 mm/rev. Current and voltage were measured using a digital wattmeter in real-time, and energy consumption was calculated in wattseconds (Ws) using power calculation formulas. The results indicate that increasing the feed rate and spindle speed leads to higher instantaneous power consumption. However, total energy consumption tends to decrease at higher speed and feed combinations due to shorter machining times. The optimal parameter combination was found at a feed rate of 0.1 mm/rev and a spindle speed of 1280 rpm, which resulted in the lowest energy consumption of 387 Ws and the fastest drilling time. This demonstrates that selecting the right machining parameters not only improves energy efficiency but also maintains or enhances productivity. The observed power consumption pattern typically shows a sharp increase at the beginning of the drilling process, a stable phase during the main cutting stage, and a rapid decrease towards the end of the cut. These findings contribute to a better understanding of the relationship between machining parameters and energy efficiency, serving as a basis for developing sustainable production strategies in the manufacturing sector that prioritize energy savings and cost reduction.

This community service initiative aims to educate and assist in the implementation of an Internal Control System ICS at Minimarket Malika as a strategic effort to safeguard assets and enhance operational effectiveness and efficiency. The ICS applied includes a systematic recording process for inventory, purchase prices, and selling prices. These records are intended to ensure that all transactions are properly documented and accountable.Internal evaluations are conducted regularly through annual stock-taking activities, which involve verifying and matching inventory data recorded in the system with the actual physical stock in the store or warehouse. This activity serves as a critical benchmark for assessing business stability, the accuracy of inventory records, and the overall effectiveness of inventory management. Any transactional errors identified during sales operations are corrected immediately in real-time to prevent error accumulation and potential financial losses. The role of management is essential, particularly in maintaining business continuity through improved service quality and the timely fulfillment of customer needs. In response to intense competition and dynamic market changes, Minimarket Malika adopts adaptive strategies such as price adjustments, excellent customer service, and a broader product assortment to meet diverse consumer demands. To prevent fraud, the minimarket has installed CCTV cameras at strategic locations and provides training for employees on how to detect counterfeit money and suspicious behavior. The ICS also supports risk management in inventory by monitoring the movement of goods in real-time, allowing management to make accurate decisions about which products need to be stocked in accordance with current consumer demand trends.Through the consistent and comprehensive application of an internal control system, Minimarket Malika is expected to improve its competitiveness while maintaining the integrity and sustainability of its business operations amid ongoing economic challenges. Furthermore, this approach serves as a practical model for other small and medium enterprises (SMEs) aiming to strengthen their internal governance and adapt to an increasingly complex retail environment.

This study explores the key determinants of field engineer efficiency in the field service industry by analyzing the impact of self-efficacy, resource management, and time management on operational performance. Employing a quantitative research approach, data were collected using saturated sampling from 102 field engineers and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The measurement model showed robust psychometric properties, satisfying the thresholds for convergent validity, discriminant validity, and internal consistency reliability. The structural model results indicate that all three independent variables significantly influence field engineer efficiency. Self-efficacy was found to have the strongest effect (β = 0.421, p < 0.001), followed by resource management (β = 0.347, p < 0.001) and time management (β = 0.289, p < 0.001). The model accounts for 68.7% of the variance in field engineer efficiency, reflecting strong explanatory power and predictive accuracy. Among these variables, self-efficacy emerged as the most dominant factor, suggesting that field engineers' belief in their ability to perform tasks is a critical driver of operational success. High self-efficacy enhances motivation, resilience, and effective problem-solving under pressure, making it essential in dynamic and unpredictable field environments. Resource and time management also play crucial roles in supporting engineers' ability to complete tasks efficiently by ensuring optimal allocation of tools, equipment, and time. The findings provide practical implications for field service organizations aiming to improve workforce performance. Investing in training programs that strengthen self-efficacy, combined with systematic improvements in resource and time management practices, can significantly enhance operational outcomes. By prioritizing these factors, organizations can boost engineer efficiency, reduce operational costs, and improve service delivery, ultimately gaining a stronger competitive advantage in the industry.

Digitalization has been a key catalyst for change in the global business landscape, driving the transformation of companies' strategies, organizational structures, and operational models. For small and medium enterprises (SMEs), digital technology opens up great opportunities to expand market reach and compete in the international arena more effectively. Technologies such as e-commerce, social media, big data analytics, and cloud-based platforms enable SMEs to break through geographical boundaries, facilitate access to global customers, and accelerate product distribution and marketing processes. This paper explores the current academic literature that discusses the influence of digital technology on the internationalization of SMEs. A total of five relevant studies were analyzed to identify common patterns, challenges, and successful strategies in the use of digital technology. The results of the study show that the adoption of digitalization not only improves operational cost efficiency, but also encourages business model innovation, such as digital platform-based marketing, cross-border virtual collaboration, and the development of a more adaptive global business ecosystem. In addition, the ability to utilize digital technology gives SMEs a competitive advantage through access to real-time market information, personalization of offers, and more targeted branding strategies. However, the research also found obstacles, such as limited human resources, technological infrastructure, and digital literacy among SMEs. Therefore, synergy is needed between business actors, the government, and academia to support the acceleration of digital technology adoption through training, mentoring, and policies that support innovation. The paper also highlights future research opportunities, such as the integration of artificial intelligence (AI) technologies, automation, and blockchain in supporting the global expansion of SMEs. These findings are expected to be a strategic reference in designing sustainable internationalization policies in the digital era.

Photogrammetry is a widely used technique in reverse engineering that utilizes photographs taken from multiple angles to capture the geometric structure and surface textures of physical objects. This method has gained popularity due to its cost-effectiveness and time efficiency compared to more expensive alternatives such as laser scanning. However, one of the primary limitations of photogrammetry is its susceptibility to dimensional deviations that can affect the accuracy of the resulting 3D model. Among the influential parameters, the number of photos taken and the camera’s shutter speed play a crucial role in determining the level of geometric precision. This study aims to analyze the effect of the number of photos and shutter speed on dimensional deviation in 3D reconstruction results. It also seeks to determine the optimal combination of these parameters to enhance model accuracy in reverse engineering applications. The research method used is an experimental approach, in which variations of photo quantity and shutter speed are applied during image capture. The resulting photographs are processed into a 3D model using Computer-Aided Design (CAD) software and compared with the actual dimensions of the object under study. The findings reveal that both the number of photos and shutter speed significantly influence dimensional accuracy, both individually and interactively. The best results were obtained using a combination of 48 photos with a shutter speed of 0.020 seconds, yielding the smallest deviation of 7.6 mm. In contrast, a combination of 36 photos with the same shutter speed produced the highest deviation at 10.6 mm. ANOVA analysis yielded a p-value < 0.05 and an R² value of 94.21%, confirming the importance of selecting appropriate imaging parameters for accurate photogrammetry outcomes.

The food security program involving chili cultivation in Pentur Village is hindered by inefficiencies in water use and suboptimal plant growth, primarily due to traditional irrigation methods that fail to consistently maintain ideal soil moisture and temperature. This issue is exacerbated by unpredictable environmental shifts, such as fluctuating weather patterns, and a lack of precise irrigation control stemming from technological limitations. To address this, a system for monitoring and regulating chili plant irrigation using IoT technology was developed. This system employs humidity and temperature sensors connected to an IoT platform like Blynk, enabling real-time observation of plant and environmental conditions. Data on soil moisture, air temperature, and humidity are stored in a database, and irrigation is automated based on soil moisture levels. The goal is to enhance water efficiency, minimize risks associated with over or under-watering due to environmental variations, and improve both yield and quality of the chili crop. This IoT-based system aims to simplify chili plant management for Pentur Village farmers and significantly boost agricultural output.

The rapid development of information technology has had a significant impact on various sectors of life, including micro-enterprises such as meatball stalls. Amidst increasingly fierce competition and the need for operational efficiency, many micro-enterprises are shifting from manual management systems to digital systems. This study aims to explain the background, objectives, and benefits of utilizing information technology in managing meatball stalls, with a focus on the implementation of the Odoo application as a business management solution. Odoo is an open-source Enterprise Resource Planning (ERP) system that offers various functional modules such as Point of Sale (POS), inventory management, accounting, and Customer Relationship Management (CRM). Through the implementation of Odoo, meatball stalls can manage various operational aspects in an integrated manner, from recording sales transactions, managing raw material stock, financial reporting, to customer relations. The results of this technology implementation show significant improvements in data recording accuracy, service speed, and ease of decision-making based on accurate and real-time data. In addition, this technology also provides opportunities for stall owners to develop their businesses more professionally and competitively. Thus, the integration of information technology like Odoo not only improves efficiency and productivity but also contributes to economic growth by strengthening the micro-enterprise sector. This digital transformation is expected to be a strategic step in realizing a modern meatball stall that can compete in the digital era.

This study focuses on developing a web-based Research and Community Service Information System (SIPPMAS) for Politeknik Takumi Bekasi, utilizing the Waterfall methodology. The aim is to create an integrated platform that streamlines the management of research and community service activities, from proposal submission and budget allocation to project execution and final reporting. The Waterfall method was chosen for its structured, sequential approach, ensuring a systematic development process through distinct phases: requirements analysis, design, implementation, testing, and maintenance. This approach is expected to enhance data accuracy, improve operational efficiency, and provide real-time project monitoring, ultimately facilitating better collaboration among stakeholders and increasing the overall impact of research and community service initiatives at Politeknik Takumi Bekasi. The system is designed to address current manual administrative challenges, offering a centralized and accessible solution for all users.

This study analyzes the influence of solar panel type and solar charging technology on the charging performance of lithium-ion batteries. Two types of solar panels, monocrystalline and polycrystalline, were tested alongside two charging technologies: Maximum Power Point Tracking (MPPT) and Pulse Width Modulation (PWM). Experiments measured voltage, current, and charging time parameters, and calculated the State of Charge (SoC) as a performance indicator. The results showed that the combination of monocrystalline panels with MPPT technology achieved the highest charging efficiency and shorter charging times compared to other combinations. These findings indicate that selecting the appropriate panel type and solar charging technology significantly affects lithium-ion battery charging performance, providing valuable considerations for portable solar energy system designs and renewable energy applications.

 The Karanggeneng River in Rembang Regency, Central Java, serves as the main water source for the surrounding community but is vulnerable to seawater contamination during the dry season due to decreasing river elevation. To address this issue, this study aims to design and implement a river water elevation monitoring device based on the Internet of Things (IoT) powered by a hybrid Solar Power Plant (PLTS). The device utilizes the MB7360 ultrasonic sensor connected to an ESP32 microcontroller to measure water elevation in real-time and display the data through an LCD and the Blynk application on a smartphone. The methodology includes literature review, device design, system implementation, and field performance testing. Test results show that the sensor can measure water height accurately within a range of 30 cm to 5 meters, and the PLTS system is capable of supplying the required 0.56 Watts of power. The study compared two alternative solutions and selected the ESP32-based system as the best option due to its efficiency, cost-effectiveness, and easy-to-source components. The conclusion of this research indicates that the developed device can provide accurate and continuous information, support monitoring of river conditions to prevent the risk of seawater intrusion, flooding, or drought, and has the potential to be applied as a mobile system in various other river locations across Indonesia.

Digitalization has become the driving force behind transformation in the logistics sector, particularly at seaports, which serve as key nodes in the global supply chain. Indonesian ports face persistent challenges such as high logistics costs and long vessel turnaround times. By implementing digital technologies such as the Port Community System (PCS), Artificial Intelligence (AI), and Blockchain, ports can enhance operational efficiency, accelerate service processes, and improve transparency and accountability. Digital systems also enable real-time integration among stakeholders, contributing to faster cargo flow and reduced national logistics costs. However, the implementation of digitalization is not without significant barriers, including limited information and communication technology (ICT) infrastructure, low digital competencies among the workforce, and high initial investment costs. Furthermore, ports face organizational cultural resistance to change and cybersecurity risks that threaten operational continuity. Smaller ports in developing countries often struggle to adopt these technologies independently due to budget constraints. To overcome these challenges, synergy between the government, port operators, and technology providers is essential. Programs such as the National Logistic Ecosystem (NLE) represent a strategic step to accelerate sustainable digital adoption. With a holistic approach encompassing technology, human resources, and business processes, digitalization can become a key catalyst in enhancing the competitiveness of Indonesian ports on a global scale.

A 300 kVA generator set is an important tool as a backup power source in many sectors. Manual monitoring of generator set performance is often inefficient and can cause delays in detecting problems. Various advances in Internet of Things (IoT) technology have enabled the design of remote monitoring systems to overcome these limitations. This study aims to develop an IoT-based monitoring tool capable of monitoring important generator set parameters such as voltage, current, power, and engine temperature in real-time. This will enhance generator set management efficiency and reduce the risk of damage. The method used is an experimental approach involving the creation of an IoT-based monitoring system prototype. Operational data from the generator set is collected using sensors and then transmitted to an IoT platform for analysis. This research uses PZEM-004T sensors to monitor parameters such as power, current, and voltage. RTD PT100 sensors monitor parameters such as engine temperature, oil temperature, and turbo temperature. Honeywell PX3 sensors monitor oil pressure. Honeywell 1GT101DC sensors monitor engine speed. The results of the study show that the device works well with an average error of 0.76% from the sensors used. The greater the distance between the Wi-Fi modem and the device, the slower the data response speed.

Airports serve as a central hub for air transportation, requiring precise coordination and operations, including ground handling services. One key element is the Ground Support Equipment (GSE) personnel, who are responsible for aircraft support equipment. They must adhere to Standard Operating Procedures (SOPs) to ensure performance meets safety and efficiency standards. However, challenges such as timeliness, procedural discrepancies, and inconsistencies in SOP implementation remain. This study used a quantitative approach with correlational analysis and simple linear regression. The sample consisted of 30 GSE personnel selected through total sampling, and data were collected through a questionnaire that had been tested for validity and reliability. This method aimed to identify the effect of SOP compliance. The results showed that SOP compliance had a positive and significant impact on GSE officer performance at Sam Ratulangi Airport in Manado. The regression coefficient of 0.632 indicates a positive relationship, with a significance value of 0.002 indicating statistical significance. The coefficient of determination (R Square) value of 0.241 indicates that 24.1% of the variation in officer performance can be explained by compliance with SOPs, which indicates that increased compliance contributes positively to their performance.

X Health Center has implemented EMR on SIMPUS since 2009-2010. However, from the preliminary study, it was found that there were obstacles such as network trouble, long loading when many users were pulling data on the system, and there was no SOP for down time: The purpose of this study is to analyze the implementation of Electronic Medical Records at X Health Center, Semarang City in the aspects of Human, Organization, Technology, Net-benefit.  Methods: This study used a descriptive qualitative approach with interviews, observations and documentation studies. Results: The results of research at X Health Center show that there are problems in implementing EMR at X Health Center, in the human aspect, namely system training is still given only to representative officers such as IT and SIK staff. In the organizational aspect, namely limited facilities and lack of manpower. On the technology aspect, namely internet network instability, inconsistent electricity supply and generator unpreparedness and hardware limitations. While in the net-benefit aspect, the implementation of EMR has an impact on increasing the efficiency and effectiveness of X Health Center services. Conclusion: The implementation of electronic medical records at X Health Center is not yet fully optimal, namely in the aspects of human, organization and technology.