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This study aims to analyze the effect of using multi-platform accounting on the timeliness and accuracy of financial reporting at PT XYZ, a service company engaged in the distribution of cement. In carrying out its operations, this company uses three different types of accounting applications in the financial recording process, namely Microsoft Excel, Accurate and Semenku. This study uses a descriptive qualitative research method and data collection through observation. The results of the study indicate that the use of multiple platforms simultaneously can cause data inconsistencies and slow down the financial reporting process, but on the other hand it also provides flexibility in recording transactions. Therefore, system integration or evaluation of platform use is needed to improve the efficiency and accuracy of financial reporting.

Arbuscular Mycorrhizal Fungi (AMF) are biological agents that play an important role in increasing the efficiency of nutrient uptake and plant tolerance to abiotic stress, especially in acidic soils such as ultisols. This study aims to analyze the growth and yield responses of chili (Capsicum annuum L.) to the combination of NPK fertilizer doses and AMF inoculation. The study was conducted in Sungai Talang, Gadut, Agam Regency, from June to October 2025 using a Factorial Completely Randomized Design with two factors, namely AMF inoculation (without AMF, Glomus sp., and Rhizophagus sp.) and NPK fertilizer doses (100%, 75%, 50%, and 25% of the recommendation). The results showed a significant interaction between AMF inoculation and NPK doses on plant height, dry weight, flowering time, and fruit yield per plant. Glomus sp. inoculation with a 50% NPK fertilizer dose resulted in the highest growth and yield, equivalent to the 100% NPK treatment without AMF. The integration of AMF with a 50% reduction in NPK dosage has been shown to maintain crop productivity. This strategy can serve as a basis for developing a sustainable agricultural system based on nutrient efficiency and soil microbial balance.

This research aims to develop a digital-based governance model for village finance to support the realization of a Smart and Green Village. The study analyzes how digital transformation in village finance management can increase transparency, accountability, and efficiency, while promoting sustainability-oriented budgeting and environmental practices. A Systematic Literature Review (SLR) was used to identify, evaluate, and synthesize scientific publications from 2022 to 2025, accessed through reputable databases such as ScienceDirect, Springer, Wiley, Taylor & Francis, SAGE, ACM, and IEEE. The review focused on topics including digital governance in villages, digital public finance, smart village development, green budgeting, environmental sustainability, and rural digital transformation. Findings indicate that digital-based village finance governance enhances administrative efficiency, strengthens budget transparency through real-time monitoring, minimizes financial deviation risks, and boosts public participation in fiscal accountability. Integrating digital systems with green budgeting features enables the prioritization of sustainable programs, such as renewable energy, waste management, climate change mitigation, and green infrastructure development. The study suggests a comprehensive digital-based governance model that includes e-budgeting, e-accounting, digital payment systems, public transparency dashboards, and environmental performance indicators to support the implementation of a Smart and Green Village. This research offers strategic insights for village governments, policymakers, and practitioners on the importance of adopting digital governance tools to improve financial management and strengthen sustainable development at the local level.

Manual post-harvest paddy stirring requires significant time and labor and often results in uneven mixing, which can affect grain quality. To address this issue, this study designed and implemented a prototype of an Internet of Things (IoT)-based paddy stirring robot to simplify the process and improve efficiency. The system utilizes an ESP32 microcontroller as the main controller, DC motors as the stirring mechanism, and an IoT module for wireless connectivity to a mobile application. The research stages included hardware design, control system programming, IoT platform integration, and performance testing. Testing was conducted to evaluate response time, mixing uniformity, and power consumption. The results showed that the system could be operated remotely via a local Wi-Fi network with an average delay of less than 1 second, enabling real-time control. The prototype successfully stirred 0.3 kg of paddy with a mixing uniformity rate of 92% and an average power consumption of 12 watts. The application of IoT in the paddy stirring mechanism significantly improved time efficiency, reduced manual labor requirements, and maintained grain quality compared to traditional methods. These findings indicate the potential for further development into a large-scale automated paddy processing system with integrated humidity and temperature sensors for real-time quality monitoring, supporting the modernization of post-harvest processing through digital technology.

This research aims to analyze the implementation of the Accurate accounting system in the cash transaction recording process at PT XYZ, a cement distributor company focused in eastern Indonesia, particularly in East Nusa Tenggara. Along with business growth, the company transitioned from manual recording using Microsoft Excel to a computerized system to enhance efficiency and accuracy. This study employs a descriptive qualitative method with data collection techniques through interviews, observations, and documentation. The analysis focuses on comparing processes before and after the use of Accurate, its contribution to efficiency, and the challenges faced during implementation. The research results show that the Accurate system significantly improves efficiency by automating journal processes, minimizing human error, and presenting financial data in real-time and structured formats. However, challenges related to discipline in timely transaction input were found, causing discrepancies between system balances and bank statements. The solution to these challenges is to improve the finance team's discipline in performing daily data input.

The advancement of digital technology has driven many service companies to transform toward faster, more efficient, and accurate systems. Himeji Express Banjarmasin, a company engaged in the field of goods delivery services, still faces challenges in data management and service processes that are mostly carried out manually. This condition leads to delays in shipment tracking, data entry errors, and limitations in report generation. To address these issues, a digital application was designed to optimize the delivery service processes at Himeji Express Banjarmasin. The application was developed using the Unified Modeling Language (UML) approach to model system requirements through use case, activity, sequence, and class diagrams. The implementation process utilized Sublime Text and XAMPP software, supported by an integrated database. The results show that the developed digital application can improve the effectiveness of managing customer, employee, pricing, cargo, and transaction data while generating automatic and real-time reports. This application enhances operational efficiency, transparency, and responsiveness to customer needs at Himeji Express.

Waste management remains a major challenge, particularly due to the lack of public awareness and habits in sorting waste from its source. Innovative technology-based solutions are needed to support more effective waste management systems. This study aims to design and develop an Internet of Things (IoT)-based smart trash bin capable of automatically sorting metal and non-metal waste. The system utilizes an ESP32 microcontroller as the main controller, an LJ12A3-4-Z/BY sensor to detect metal materials, an E18 sensor to detect non-metal materials, and an ultrasonic sensor to monitor bin capacity. The waste separation mechanism is operated by a servo motor controlled by the system, while the Blynk application is integrated for real-time monitoring and full-capacity notifications sent directly to the user’s smartphone. The research stages included hardware design, microcontroller programming, IoT platform integration, and functionality testing to ensure system performance and reliability. The results showed that the smart trash bin operated as expected, successfully identifying and separating metal and non-metal waste automatically, while also sending real-time notifications to the user when the bin approached full capacity. The implementation of this technology has the potential to modernize waste management processes, improve the efficiency of waste sorting, and reduce dependency on manual labor. Furthermore, this research opens opportunities for future development by integrating additional sensors and cloud-based data management systems to support smart city initiatives and sustainable waste management practices.

This study aims to analyze the e-invoice creation procedure in the management of “zak” cement transportation at PT Semen Indonesia Logistik (SILOG), as part of the digital transformation in the billing system based on the urgency of the company's need for a more efficient and accurate billing system to reduce the risk of late payments and improve operational efficiency. This study uses a descriptive qualitative approach with data collection techniques through in-depth interviews, direct observation, and documentation of four informants involved in the e-invoice creation process. The e-invoice creation procedure at SILOG involves the integration of the CSMS, FIOS, SAP, and PORTAL systems. The results of the study indicate that the implementation of e-invoices brings a number of advantages such as accelerating the billing process, time efficiency, reducing dependence on physical documents, and increasing data accuracy through a computerized system. However, this study also found significant technical constraints, especially in the accuracy of geofence data and unloading destinations that impact the validity of e-invoices. The FIOS system that is not yet optimal causes vehicle location data to sometimes not match the unloading point that should be. This constraint requires additional manual processes that can hinder the effectiveness of the system. Therefore, this study recommends improving the information system and technical training for users to reduce errors and increase the effectiveness of e-invoice use as a whole.

This study aims to analyze the efficiency of issuing tax invoices and reporting Value Added Tax (VAT) Periodic Tax Returns (SPT Masa PPN) by comparing the DJP Online system and the Coretax Administration System at CV XYZ. The research focuses on comparing the reporting process before and after the use of the Coretax digital system, as well as evaluating its direct impact on the efficiency of VAT reporting for Taxable Entrepreneurs (PKP). A descriptive qualitative method was used, with data collected through observation and documentation. The results show that prior to using Coretax, tax reporting was conducted through two separate applications, e-Faktur and e-SPT, which led to inefficiencies, input errors, and longer processing times. After the implementation of Coretax, the reporting process became more integrated, automated, and time-efficient. The system also supports digital document archiving and offers automatic validation and notifications, thereby reducing the risk of delays and reporting errors. Although technical issues such as internet dependency, system errors, and user adaptation remain, Coretax overall has a positive impact on improving tax administration efficiency and compliance at CV XYZ.

This study aims to analyze production performance and the factors influencing the productivity of mining operations at PT. XYZ during August 2025. The evaluation covers production achievement against the corporate work plan (RKAP) and the owner’s operational plan, equipment availability (Physical Availability), the productivity of loading and hauling units, and various types of loss time that reduce effective working hours. The results indicate that production realization reached only 65% of the RKAP target, while achieving 102% of the owner’s plan for total material. Low equipment availability, high loss time such as no hauler, wait operator, and front preparation, as well as the underperformance of 80-ton and 100-ton units, were identified as the main contributors to production deviation. Additional influencing factors include unit reassignment, suboptimal haul road conditions, and insufficient operational fleet numbers. The study recommends optimizing fleet management, enhancing preventive and predictive maintenance programs, reorganizing hauling workflows, and controlling dominant loss time sources to improve operational efficiency and production target achievement in future periods.

This study presents the integration of a Large Language Model (LLM) Ollama with the OpenStreetMap (OSM) API within a Business Intelligence (BI) framework to develop an intelligent, location-based recommendation system. The system is designed to assist users in finding dining, leisure, and resting places through natural language interaction and contextual understanding. The LLM interprets user input semantically, transforms it into structured spatial queries, and retrieves relevant geospatial data from OSM. The data are then analyzed, categorized, and visualized using BI methods to enhance interpretability and decision-making. The system was implemented using Next.js, Leaflet.js, ensuring interactivity and scalability for web-based deployment. Technical evaluation focused on system accuracy, response time, and output consistency. Results demonstrate an average response time of 1.74 seconds, 80% accuracy, and 80% consistency, proving the model’s efficiency in producing relevant, context-aware recommendations. This integration highlights the potential of combining open geospatial data, local LLMs, and BI analytics to create intelligent, data-driven decision support systems applicable to tourism, urban planning, and spatial information management.

Indonesia is one of the countries with abundant availability of palm fiber composite, yet its application in advanced material technology remains limited. On the other hand, most motorcycle helmets available in the market are made from ABS plastic, which has limitations in impact energy absorption and may increase the risk of head injuries during accidents. This study aims to develop helmet composites based on palm fiber and epoxy resin by varying the fiber volume fractions (15%, 25%, and 35%) and alkali soaking durations (75, 150, 225, and 300 minutes). The impact strength test results showed that the combination of 35% fiber volume and 225-minute alkali soaking produced the highest specific impact energy (SIP) of 0.142 J/mm². As a comparison, SNI-compliant helmets made from ABS plastic only reached an EPS value of 0.00972 J/mm², indicating that palm fiber-based composite helmets could improve impact energy absorption efficiency by more than 14 times. The results conclude that increasing the fiber volume fraction and optimizing the alkali treatment duration significantly enhances the impact resistance, making ijuk-based composite helmets a promising alternative for safer and more eco-friendly protective gear.

Overburden removal is a critical phase in coal mining operations, as it directly affects production continuity and operational efficiency. However, production realization often deviates from the mine plan due to various operational constraints. This study, conducted at Pit K1 Mahakam of PT. Insani Baraperkasa, evaluates the causes of underachievement in overburden stripping targets using the Six Big Losses framework, which classifies inefficiencies into Breakdown Losses, Setup and Adjustment Losses, Idling and Minor Stops, Reduced Speed Losses, Process Defect Losses, and Reduced Yield Losses. The analysis revealed that the dominant losses were Reduced Speed Losses (26%) and Setup and Adjustment Losses (10%), primarily caused by disposal congestion, shift changes, and repairs at the loading and disposal areas. Minor contributions were found from idling (3%), production losses (5%), while breakdown losses showed negligible impact. These factors led to increased standby time and reduced equipment cycle effectiveness. Improvement strategies are recommended through optimized disposal allocation, reduction of waiting time, and stricter control of external operational disruptions to enhance stripping efficiency and achieve production targets.

In the digital era, the demand for practical and efficient security systems has significantly increased, particularly in the context of access control for restricted rooms or buildings. This research aims to develop an automatic door locking system utilizing an RFID card and a NodeMCU ESP32 microcontroller integrated with Internet of Things (IoT) technology through real-time notifications using the Telegram application. The system is designed to replace conventional locking methods that often present various weaknesses, such as key loss, physical duplication, and lack of remote access capabilities. The development method employed is the Research and Development (R&D) approach, consisting of needs analysis, system design, hardware and software implementation, followed by testing and evaluation. The main components used in the system include the RC522 RFID reader for user identification, Espressif manufactures the ESP-32 microcontroller, which is equipped with Wi-Fi and Bluetooth modules to enable wireless internet connections. NodeMCU ESP32 as the control center and internet connector, a relay module as an electronic switch, and a solenoid door lock as the actuator. The results show that the system is capable of accurately reading RFID card UIDs, granting access to registered cards, activating the solenoid to unlock the door, and sending access status notifications to Telegram in an average of less than three seconds. The system also effectively denies access to unregistered cards and sends warning messages accordingly. Therefore, this system enhances the security and efficiency of room access control and has the potential to be adopted as a prototype solution in the development of smart homes or modern access control systems.

The rapid development of network infrastructure demands high Quality of Service (QoS), especially in Metro Ethernet networks widely utilized by telecommunication service providers. A primary challenge is efficient bandwidth management to ensure network stability and performance. This research aims to optimize bandwidth management by implementing the Y.1731 method based on Ethernet Operations, Administration, and Maintenance (OAM) on Raisecom devices. The methodology employed is a quantitative experimental approach based on technical simulation within an Professional Network Emulator Tool Lab (PNET Lab), where real-time network performance measurements are conducted using the ITU-T Y.1731 protocol for key parameters such as delay, jitter, and packet loss on Raisecom devices (represented by Cisco routers). The expected outcomes include increased efficiency in bandwidth utilization through more adaptive allocation, comprehensive and accurate real-time network performance monitoring capabilities, validation of OAM functions on Raisecom devices, improved Quality of Service (QoS) and better Service Level Agreement (SLA) attainment, and the provision of technical recommendations for network management. The implementation of Y.1731 is anticipated to quickly detect and respond to service degradation, thereby providing a strong basis for decision-making in network management and contributing to the enhancement of service quality in Metro Ethernet networks through optimization based on proactive monitoring.

Android continues to innovate, and biometric systems particularly fingerprint sensors must operate with high efficiency. However, the main challenge lies in the communication between hardware and software, which often causes high latency, excessive power consumption, and protocol incompatibility between components. As a result, authentication speed decreases and system stability is compromised, especially on mid- to low-range devices. This study explores various implementations of Android-based fingerprint systems, focusing on how sensor modules interact with the microcontroller or Trusted Execution Environment (TEE) and the operating system through a hardware-software co-design approach to evaluate integration efficiency across all layers. The analysis reveals that conventional protocols such as Bluetooth or serial connections still cause delays, while improvements in drivers and the Hardware Abstraction Layer (HAL) can significantly reduce latency. As a solution, the researchers propose a co-design optimization approach that utilizes data flow normalization within the HAL and adopts lightweight communication protocols to accelerate the verification process. Based on the test results, this approach successfully improves efficiency—authentication time is reduced by up to 35% and power consumption decreases by approximately 15%. Therefore, the efficiency of communication between hardware and software becomes a key factor in enhancing the performance and reliability of fingerprint systems on Android devices.

The synchronization of mutex and semaphore mechanisms is an important technique in operating systems for managing concurrent resource access in multi-threaded environments. In the Android operating system, which relies on thread-based programming to maintain performance and responsiveness, these two mechanisms play a vital role in preventing race conditions and ensuring data integrity. A mutex is a locking object that ensures that only one thread can access a specific resource at a time, while a semaphore controls access to a limited number of resources by counting the number of threads that can access them simultaneously. In Android, these mechanisms are implemented using the Lock class for mutexes and the Semaphore class for semaphores, both of which can be used to control synchronization between threads in Android applications. This paper will discuss the application of these two mechanisms in the context of shared resource management, as well as a comparison of their performance and advantages in dealing with complex multi-threading scenarios on Android. Emphasis will also be placed on the challenges faced in using these two mechanisms in Android applications, as well as how proper programming can avoid deadlocks and improve application efficiency.

In the modern industrial world, robots like mechanical arms in automotive factories or packaging lines must move quickly and safely. For this, a real-time operating sistem (RTOS) is needed—think of it as a "super-fast brain" that ensures the robot reacts instantly to commands, without delays or errors. This paper analyzes popular RTOS like FreeRTOS and VxWorks for controlling industrial robots, focusing on evaluating performance (speed of operation) and stability (long-term reliability). We conducted tests in a lab using a simple robot that moves its arm to pick up objects. Performance was measured by response time (how quickly the robot stops when encountering an obstacle, ideally under 10 milliseconds) and throughput (how many tasks it can complete per second). Stability was checked through simulations of disruptions, like heavy loads or interfered sensor signals, using metrics such as error rate and time variation (jitter). Results show that FreeRTOS is more efficient for small, affordable robots, with high performance (average response time of 4 ms) but moderate stability (5-10% errors during overload). In contrast, VxWorks excels in stability (errors <2%, stable for up to 95% of tasks on time) for large factory robots, though it requires stronger hardware. Our analysis uses simple models like graphs and repeated tests, without complex formulas, to prove that the right RTOS can boost production efficiency by up to 25% and reduce accident risks.

PT. YGI, an automotive manufacturing company, uses the Press Injection GB-36 machine in its production process. However, this machine frequently experiences failures, causing high downtime and reduced production efficiency. This study aims to identify the types of failures, determine the most critical components, and propose a maintenance system using the Reliability Centered Maintenance (RCM) approach. The method used is descriptive qualitative, involving FMEA (Failure Mode and Effect Analysis), Logic Tree Analysis (LTA), and maintenance action selection. Data were collected through observations, historical failure documentation, and interviews. The analysis results indicate that components such as the injection nozzle, heating, and clamping are the most critical, contributing over 80% of total failures based on Pareto analysis and the highest RPN values in FMEA. Proposed maintenance actions include Condition Directed and Time Directed approaches. Additionally, the maintenance system is supplemented with standard operating procedures (SOP) and routine inspection schedules to improve machine reliability and reduce production downtime. This study is expected to enhance the efficiency and productivity of the Press Injection GB-36 machine at PT. YGI through the appropriate implementation of RCM.

Conventional attendance systems often face various problems such as inefficiency, inaccuracies in attendance logging, and limitations in recapitulation processes. Manual systems are prone to human error and time-consuming, while fingerprint-based systems may fail when the sensor is affected by dirty, wet, or damaged fingers. This study aims to develop an attendance system based on Artificial Intelligence (AI) by utilizing the face_recognition function in Python and implementing a microservice architecture to improve efficiency and accuracy in attendance recording. The system is developed using the Agile Feature-Driven Development (FDD) method, which focuses on building system features based on prioritized business values. This method is applied within the Software Development Life Cycle (SDLC) to ensure a structured, iterative, and user-oriented development process. Facial recognition is performed by comparing the encoding of the captured face image with the data stored in the database. The results show that the system is capable of recording attendance automatically, accurately, and in real-time. Furthermore, the recapitulation process becomes more efficient as the system manages and presents the data systematically.