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Work volume calculations are essential for project cost estimation. Many projects, such as the Laboratory Building of the Faculty Engineering at Tanjungpura University, calculate work volumes conventionally. Conventional calculation considered less efficient and prone to errors. Building Information Modeling (BIM) provides a solution that produces more accurate and efficient calculations than conventional methods. This research aims to compare structural work volume results produced by BIM using Autodesk Revit against conventional methods and project’s BOQ. This research also describes the benefits and challenges of BIM implementation based on the researcher’s experience applying BIM with Autodesk Revit in work volume calculation. The comparison between BIM and conventional method shows a maximum difference of 2% across all work items. Meanwhile, the comparison between BIM and the BOQ shows significant differences: 81% in column formwork area, 24% in grade beam/beam concrete volume, 25% in column reinforcement weight, 25% in steel beam weight, and 10% in the steel plate weight. This research proves that BIM implementation produces more accurate and efficient calculations and serves as an effective BOQ cross-check tool. Based on the researcher’s experience in implementing BIM with Autodesk Revit, challenges found in procurement aspects, modeling aspects, and model dependency on reference drawings.    

This community service program aims to optimize construction project planning through assistance in preparing a business feasibility study at PT Sahabat Anugrah Sejati. The construction sector is a strategic industry that requires effective resource management, proper risk mitigation, and accurate planning to ensure project success. Therefore, the program supported the partner in analyzing financial, managerial, market, and economic aspects prior to making investment decisions for the proposed project. The results show that the project is feasible based on the Net Present Value (NPV) and Internal Rate of Return (IRR) analyses. An efficient organizational structure, a competent management team, and strong supervision mechanisms further strengthen the project’s operational readiness. Increasing demand for construction services also enhances the company’s market prospects. However, several areas still require improvement, including heavy equipment utilization, material efficiency, and digital marketing strategies. This program provides strategic recommendations to help PT Sahabat Anugrah Sejati improve project feasibility, operational effectiveness, and long-term business sustainability.

Innovation in biology learning is increasingly necessary, as conventional instructional practices are often dominated by memorization-based methods that limit students’ active engagement and critical thinking development. Along with rapid advances in science and technology, digital applications offer new opportunities to enhance teaching and learning processes. One such application is Canva, a digital design platform that can be utilized as an effective learning media to support teachers and students in biology education. This study aims to describe the implementation of Canva-based learning media through a training program conducted at SMA Islam Terpadu Daarul Rahman and to examine its perceived usefulness for both teachers and students. The training involved teachers in developing biology learning materials using Canva by integrating visual elements, images, and videos to present complex biological concepts more clearly. The results of the training indicate that Canva is considered practical, user-friendly, and efficient by teachers in designing learning materials. Teachers reported that the application helped them present content in a more attractive and structured manner. Furthermore, students benefited from the use of Canva-based materials, as they demonstrated better understanding of the subject matter and increased interest in learning biology. The integration of visual and multimedia elements also supported the development of students’ critical thinking skills by encouraging analysis and interpretation of biological phenomena. Overall, the use of Canva as a learning medium shows potential to enhance the quality of biology learning and foster more meaningful learning experiences.

This study analyzes the conditions of extreme overcapacity in an installed exhaust ventilation system (Qinstalled = 18.00 /minute) that serves four acid cabinet units, specifically for the storage of volatile Hazardous and Toxic Materials (B3) such as toluene and methanol in tightly sealed containers. Although high capacity ensures safety, this practice causes significant energy inefficiency and unnecessary negative pressure problems in the room. Based on engineering analysis using a conservative Air Change Rate (ACR) standard of   for liquid storage of 1.38 /minute. By applying the industry standard safety factor (FoS) of 1.5, the ideal flow rate (Qideal) that must be allocated is 2.07 . The optimization analysis concludes that the currently installed system is theoretically capable of safely and efficiently serving 8 units of volatile storage acid cabinets, with the addition of 4 new cabinets to maximize efficiency and reduce energy waste. This utilizes 92% of the total capacity while maintaining a safety factor above 1.5.

The development of digital technology has driven significant changes in people's transaction patterns, including the increased use of app-based financial services. This study aims to analyze the role of the DANA app in increasing the convenience of cashless transactions in Indonesia. The method used was a literature review, analyzing journals, reports, and official documents related to the use of digital wallets and the development of DANA services over the past three years. The results show that DANA contributes to accelerating transaction processes, increasing accessibility to financial services, and providing secure and efficient payment features. Features such as QRIS, flexible balance top-ups, instant transfers, and integration with various public and commercial services have proven to facilitate users' cashless transactions. However, challenges remain, including unequal digital literacy, data security risks, and network limitations in some regions. Overall, the DANA app plays a crucial role in accelerating the digital payment ecosystem and increasing transaction convenience for the Indonesian people.

Community service activities in traditional fish ponds on Tibi Island, Tarakan, aim to increase the productivity of fish and shrimp farming using a simple yet effective approach. The methods applied include manual pond maintenance, such as spreading molasses solution (EM-4) to improve water quality, removing pests such as snails and oysters, and routine net maintenance and water drainage. Feed management is carried out every three days to maintain the nutritional balance of fish and shrimp. Although without the use of sophisticated technology, the success of cultivation depends heavily on the experience and thoroughness of the farmers in managing the pond environment. Overall, this activity demonstrates that a simple and structured approach can support sustainable cultivation, increase productivity, and strengthen collaboration between the implementation team and the pond owners. It is hoped that this method can serve as a useful example for other traditional fish farmers in increasing aquaculture yields and supporting more efficient and environmentally friendly farming practices.

Flower disease detection is a significant challenge in modern agriculture, particularly with factors such as changes in leaf color, petal shape and structure, and environmental conditions affecting the accuracy of conventional models. These factors make it difficult to achieve optimal results using traditional methods. Transfer learning is an effective solution to improve image detection performance, especially when data is limited. This study used several pre-trained models, namely VGG16, ResNet50, and EfficientNet-B0, to detect three types of flower diseases: black spot on roses, white powdery mildew, and leaf rust. The research process included data processing, increasing the data volume using augmentation techniques, model training, and evaluation of the results. Experimental results showed that the EfficientNet-B0 model produced the highest accuracy of 97.2%, significantly better than the CNN model built from scratch with an accuracy of 85.1%. This study demonstrates that transfer learning is highly effective in improving the accuracy of flower disease detection, making it a more reliable alternative to methods that do not utilize pre-trained models, especially for agricultural applications that require high levels of accuracy in disease detection.

This study aims to determine the ideal stocking density of catfish using the triple integral method. This mathematical method is applied to accurately calculate the volume of the cultivation pond and analyze the stocking amount and biomass projection at three different density levels, namely 50, 75, and 100 fish/m³. The calculation of the volume of the pond measuring 27 m x 11 m x 1.5 m produces a value of 445.5 m³. Based on the integral calculation, the optimal stocking amount is 22,275 fish, 33,413 fish, and 44,550 fish for each density, with the final biomass projection reaching 300.7 kg, 451.1 kg, and 600.4 kg, respectively. The analysis shows that the density of 100 fish/m³ produces the highest biomass, but its application must consider technical factors such as water quality, oxygen availability, and food competition. This method provides a solid and practical mathematical foundation for more efficient, scalable, and sustainable aquaculture planning.

The rapid development of the Internet of Vehicles (IoV) has introduced new security challenges, particularly in protecting Controller Area Network (CAN Bus) communications from cyberattacks such as Denial of Service (DoS) and spoofing attacks. This study proposes the implementation of the Extreme Gradient Boosting (XGBoost) algorithm combined with Information Gain feature selection to improve intrusion detection performance in IoV environments. The CICIoV2024 dataset, which represents both benign and malicious traffic, is used as the primary data source. The research process includes data integration, preprocessing, feature selection, data splitting, and model training using a 5-fold cross-validation approach. Experimental results demonstrate that the proposed model achieves outstanding performance, with accuracy, precision, recall, and F1-score exceeding 99.99%, and an Area Under Curve (AUC) value approaching 1.00. Furthermore, Information Gain successfully identifies the most influential CAN payload features, enhancing model efficiency without sacrificing accuracy. These findings confirm that the combination of Information Gain and XGBoost is highly effective for developing a fast, accurate, and efficient intrusion detection system in IoV networks.

This research examines the influence of road infrastructure development on local economic growth in Medan City, emphasizing its role in improving accessibility and supporting economic activities. Road infrastructure is a vital component of regional development, as it facilitates the movement of goods and services, reduces transportation costs, and enhances connectivity between economic centers. Well-developed road networks can stimulate business expansion and encourage investment by creating a more efficient economic environment. The study employed a descriptive quantitative approach using field surveys involving 20 respondents, including business actors, local residents, and government representatives. Data were collected through structured questionnaires and analyzed descriptively to capture perceptions regarding the economic impact of road infrastructure development. The results indicate that improvements in road quality, capacity, and connectivity have a positive influence on local economic growth. Respondents reported increased trade activities, improved access to markets, higher investment opportunities, and rising community income levels as direct benefits of improved road infrastructure. However, the study also identified several challenges that may hinder long-term economic outcomes. Traffic congestion, uneven infrastructure development across areas, and inadequate routine maintenance were highlighted as significant issues. These problems can reduce efficiency and limit the sustainability of economic gains. Therefore, continuous government commitment, effective maintenance strategies, and equitable distribution of infrastructure development are essential. Strengthening coordination among stakeholders is also necessary to ensure that road infrastructure development supports inclusive and sustainable local economic growth in Medan City.

The principle of comparative advantage explains that every country or society, like individuals, can gain benefits from their trade activities by exporting goods or services in which they have a major comparative advantage and importing goods or services in which they do not. Based on the law of comparative advantage, even though a country may be less efficient (having an absolute disadvantage) compared to other countries in the production process, the structure of industrial performance can be seen through the analysis of industrial sector behavior analyzed through various strategies such as Price, Product, and promotion. The theory of comparative advantage related to the exchange of goods is relevant as long as the traded goods are still useful. In other words, Performance is defined as the result of activities influenced by the structure and behavior within the industrial sector, where these results are often measured by the size of a company's market share or profitability in an industry. In more detail, performance can also be reflected in the form of efficiency, development (including market expansion), job creation, employee welfare, and a sense of group pride.

SMP Negeri 5 Merlung is a public junior high school in Merlung Subdistrict that has utilized the DAPODIK system for online data processing management, enabling efficient sending and receiving of information to the government. This research analyzes IT governance on the DAPODIK system using the COBIT 5 framework, specifically the MEA01 domain (Monitor, Evaluate and Assess Performance and Conformance), which focuses on monitoring and evaluating performance and conformance. The research background is based on the need to maximize the utilization of the system at the school level. The main objectives are to determine the current and expected capability levels, as well as to provide improvement recommendations to achieve higher process maturity. The research method applies Assessment Process Activities, covering observation, interviews, identification of findings, gap analysis, and recommendations. The results show that the current capability level is at level 3 (established process), while the expected capability level is directed toward level 4 (predictable process). The implications of these findings provide practical recommendations such as routine monitoring enhancements, staff training, and integration of automation tools to bridge the capability gap, thereby improving the effectiveness of IT governance at SMP Negeri 5 Merlung sustainably.

Posyandu (Integrated Health Post) is a public health facility that plays a vital role in providing health services for toddlers and pregnant women. However, data management and reporting often face challenges, such as limited access to information and errors in data recording. Therefore, this study aims to develop a Web-Based Posyandu Payolaumbu Service Information System using the CodeIgniter Framework to improve efficiency and accuracy in data management and reporting. In the development phase, a system requirements analysis and web-based application architecture design were conducted. The system implementation uses the CodeIgniter Framework as a framework to produce a faster, more efficient, and more reliable application. Proposed features include recording health data for toddlers and pregnant women, immunization schedules, weighing, and health reports. The results show that the Web-Based Posyandu Payolaumbu Service Information System can improve efficiency in recording and reporting health data. Users, including posyandu officers, midwives, and administrators, can easily access and manipulate data in real-time. Furthermore, this system helps improve service quality by providing more accurate and complete information on toddler health. In conclusion, the implementation of the Web-Based Posyandu Payolaumbu Service Information System using the CodeIgniter Framework provides significant benefits for data management and health services at Posyandu Payolaumbu. Suggestions for further development include maximizing system utilization, developing additional features, routine maintenance, and ongoing evaluation based on user feedback. With these steps, it is hoped that this system can contribute more effectively to improving the quality of health services at Posyandu and supporting comprehensive public health efforts.

Public complaint services are an essential part of public service delivery in supporting the government’s rapid response to various social issues and emergency situations. In West Tanjung Jabung Regency, public complaint services are provided through the HALO USTAD 112 Call Center managed by the Department of Communication and Informatics. However, the existing service still faces several limitations, including the lack of optimal integration in complaint data management, inadequate documentation of reports based on regional classifications, and limited capabilities in storing and retrieving complaint data. This study aims to optimize the HALO USTAD 112 Call Center service through the design of a mobile-based public complaint information system, so that the processes of receiving, managing, and monitoring reports can be carried out more effectively and in a structured manner. The system development applies the Waterfall method, which consists of requirement analysis, system design, implementation, and testing stages. The designed information system includes key features such as user and admin login, complaint submission, report management and verification, report monitoring, statistical visualization of complaint data, and regional-based report recapitulation. The application is developed using the Flutter framework with the Dart programming language, while Supabase is utilized as the backend integrated with a PostgreSQL database. The results of this study are in the form of a system design and prototype that are expected to improve the quality of public complaint services and support more accurate, integrated, and efficient data management.

Information technology (IT) governance plays a strategic role in supporting the achievement of organizational goals, especially in higher education institutions. Adiwangsa University Jambi, as a private university, is required to manage IT effectively, efficiently, and in line with the institution's vision. This study aims to analyze the level of IT governance capabilities at Adiwangsa Jambi University using the COBIT 2019 framework with a focus on the EDM (Evaluate, Direct, Monitor) domain. The research method used is a descriptive quantitative method through data collection using questionnaires, interviews, and documentation studies. The results show that the level of IT governance capability in the EDM domain is at level 2 (Managed Process), indicating that the IT governance process is running but still needs improvement in several aspects, especially in monitoring and controlling IT performance. This study is expected to provide recommendations for Adiwangsa University Jambi in improving IT governance in a sustainable manner.

This study aims to classify customer payment methods at 17 Coffee & Eatery using machine learning algorithms, namely Naïve Bayes and Support Vector Machine (SVM). The increasing use of digital and non-cash payments has generated large volumes of transaction data that are rarely analyzed optimally, even though such data contain valuable information for business decision making. This research used secondary transaction data collected from January to March 2025, consisting of 10,147 transaction records. The dataset included several attributes such as order time, payment time, transaction type, total sales, number of items, and payment method. Data preprocessing was performed through data cleaning, feature engineering, normalization, and label encoding before being divided into training and testing sets with an 80:20 ratio. The Naïve Bayes and SVM models were then trained and evaluated using accuracy, precision, recall, F1-score, and ROC–AUC metrics. The results show that both algorithms were able to classify payment methods effectively, but SVM achieved higher accuracy and more stable performance than Naïve Bayes. These findings indicate that SVM is more suitable for handling complex and heterogeneous transaction patterns. The implementation of machine learning for transaction classification can support more efficient financial management and data-driven decision making for small and medium enterprises in the culinary sector.

The implementation of the Electronic-Based Government System (SPBE) is essential for achieving efficient, transparent, and accountable village governance. Sido Rukun Village in Merangin Regency, Jambi Province, has begun using several government applications but lacks a structured enterprise architecture aligned with the national SPBE framework. This study aims to develop an enterprise architecture for SPBE in the business process domain at Sido Rukun Village. The research employs the TOGAF ADM (The Open Group Architecture Framework – Architecture Development Method) approach, involving stages such as identifying current business processes, designing a target architecture, and conducting a gap analysis between the as-is and to-be states. The findings include a business process architecture blueprint compliant with Presidential Regulation No. 95 of 2018 and Presidential Regulation No. 132 of 2022 on the National SPBE Architecture. This blueprint encompasses BPMN-based business process models and supporting artifacts that serve as a foundation for integrated information systems at the village level. The study’s implications are significant: it provides Sido Rukun Village with a practical and standardized technical blueprint for implementing a sustainable electronic-based government system, thereby supporting its transformation toward a Smart Village capable of adapting to evolving information and communication technology trends.

This study analyzes creditworthiness assessment and predicts non-performing loan (NPL) risk using the Naïve Bayes algorithm at BPR Ukabima Lestari, Jambi Branch. A quantitative data mining approach with probabilistic classification is applied. The dataset includes borrower attributes such as age, occupation, income, loan amount, tenor, collateral, and repayment history. Research stages comprise data preprocessing, model development, and performance evaluation using accuracy, precision, recall, and F1-score implemented in RapidMiner. The results indicate that the Naïve Bayes model achieves 99.58% accuracy, demonstrating strong capability to predict potential problem loans accurately and efficiently, supporting data-driven credit decisions and strengthening credit risk management in microbanking institutions.

The production sector at both the district and city levels is crucial for fostering structural change and boosting economic growth in specific areas. Still, many regions struggle with issues such as linking supply chains, readiness for technology, quality of labor, and efficient policies. This research intends to examine the strategies of the manufacturing sector at the district and city levels to enhance regional competitiveness and promote sustainable economic growth. The study utilizes a descriptive qualitative method based on a review of literature from academic journals, policy papers, and official statistics related to manufacturing progress. Results reveal that several important factors strongly affect regional manufacturing growth. These include the connection of local supply chains, industry strategies focused on the market, the implementation of digital and smart manufacturing methods, innovation encouraged by educational institutions and organizations, and the influence of local governments in developing an effective industrial policy atmosphere. Furthermore, creating designated industrial areas and managing operations efficiently significantly helps attract investments and boost the manufacturing output of regions. The research concludes that a cohesive and tailored manufacturing strategy for each region is vital for improving local productivity, generating jobs, and enhancing economic stability at both district and city scales.

Automatic motorcycle spare part sales have increased along with the high use of automatic two-wheeled vehicles in the community. To support optimal sales strategies and stock management, customer purchasing pattern analysis is required. This study uses the FP-Growth algorithm to identify association patterns between automatic motorcycle spare part products that are frequently purchased together. FP-Growth was chosen because of its ability to efficiently find frequent itemsets without the need to generate candidate itemsets as in the Apriori algorithm. Transaction data is processed to form an FP-Tree which is then extracted to find relationships between items. The analysis results show combinations of products that frequently appear together, such as brake pads and engine oil, which can be used as a basis for compiling sales packages, product placement, and product recommendations. By implementing the FP-Growth algorithm, spare part stores or workshops can improve service and efficiency in sales management.