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This study aims to develop and evaluate the feasibility of Teknoran, a website-based digital learning medium developed through the Canva application for the Office Technology subject in Grade X at SMKN 31 Jakarta. The study was motivated by learning activities that were still dominated by lecture methods and limited learning media. Teknoran was designed to facilitate learning through integrated features such as learning materials, assignments, and educational games within a single platform. This research employed the Research and Development (R&D) method using the ADDIE model, which consists of analysis, design, development, implementation, and evaluation stages. Data were collected through observation, needs analysis questionnaires, validation sheets from material and media experts, and student response questionnaires during one-to-one and small group trials. Data were analyzed using descriptive quantitative and qualitative techniques. The results showed that the Teknoran website achieved a feasibility score of 95% from material experts and 93.33% from media experts, both categorized as “Very Feasible.” Student responses also indicated a very high level of acceptance, with an average score of 95.68%. These findings demonstrate that Teknoran is highly feasible as a digital learning medium and can support more interactive, flexible, and independent learning in Office Technology subjects at SMKN 31 Jakarta.

The increasing demand for scalable and high-quality digital marketing content has exposed limitations in traditional manual copywriting processes, which are time-intensive and difficult to scale. This research proposes an adaptive AI-driven copywriting framework that integrates a full-stack web architecture with optimized prompt engineering strategies for automated content generation. The system is implemented using React.js for the frontend, Node.js with Express for backend services, and a GPT-based API for language generation. Unlike prior implementations, this research introduces a structured prompt optimization mechanism to enhance content relevance and consistency. Experimental evaluation was conducted using multiple datasets of marketing prompts, with comparisons against baseline GPT usage and manual copywriting. Quantitative results show that the proposed system achieves improvements in BLEU (+18.7%) and ROUGE-L (+21.3%) scores over baseline methods. Human evaluation involving 30 participants indicates a significant increase in perceived content quality, coherence, and persuasiveness (p < 0.05). System performance analysis demonstrates an average response time of 1.8–3.0 seconds and a GTmetrix performance score of 82%. The findings confirm that the proposed framework significantly enhances efficiency, scalability, and content quality, contributing to both applied AI systems and intelligent web-based content production.

The advancement of information technology has driven higher education institutions to manage their digital presence professionally, particularly through quality website management as a representation of institutional identity. Preliminary observations of the Universitas Graha Karya (UGK) website (ugk.ac.id) identified several issues, including inconsistent page layouts, inactive hyperlinks, and irregularly updated content. This study aims to analyze the quality of the UGK website based on three WebQual 4.0 dimensions—usability, information quality, and service interaction quality—and to determine improvement priorities using Importance Performance Analysis (IPA). A descriptive quantitative approach was employed, with data collected through questionnaires distributed to 308 active students selected via purposive sampling using the Slovin formula at a 5% margin of error. Data analysis included validity testing, reliability testing, WebQual 4.0 analysis, gap analysis, and IPA Cartesian diagram mapping. Results indicate negative grand mean gap values across all dimensions, with service interaction quality recording the largest gap (-0.16), followed by information quality and usability (both -0.01). IPA mapping identified five indicators in Quadrant I as the main improvement priorities: ease of menu navigation (U2), relevance of academic information (IQ2), clarity of information language (IQ4), website access security (SI1), and ease of contacting administrators (SI4). The study concludes that UGK's website quality has not fully met user expectations and requires structured, user-oriented improvements.

Amidst rising global pressure regarding sustainability and cross-border trade, customs agencies are no longer viewed merely as gatekeepers but as strategic actors in global environmental governance through the Green Customs Initiative (GCI). This research aims to uncover the evolutionary patterns of GCI research within the context of adaptive policy, map its intellectual structure, and identify future thematic directions. The methodology employs a bibliometric analysis of documents sourced from the Web of Science database, utilizing VOSviewer software to perform co-authorship, bibliographic coupling, and co-word analysis.The results demonstrate that the dominance of scientific actors in this field is determined more by the strength of collaboration networks than by the mere volume of publications. The findings identify that the primary intellectual foundations of GCI research rest upon the critical relationship between environmental regulation, international trade, market responses, and eco-innovation. Furthermore, country-level analysis highlights the central roles of China, the United States, and the United Kingdom in shaping the knowledge structure of this domain. Overall, these findings underscore that the GCI has evolved into a multidisciplinary field that requires an adaptive policy framework to respond to the dynamics of ecological risks and global trade demands through institutional flexibility and cross-actor collaboration. By integrating environmental protection into border management and risk assessment, this study provides a strategic reference for customs authorities to move toward a more responsive and knowledge-based green customs administration.

The increase in activity and security threats on Ubuntu server causes the volume of system logs to become very large and difficult to analyze manually. This condition potentially leads administrators to experience delays in detecting abnormal activities, such as repeated login attempts and web access patterns related to online gambling promotions. Therefore, this research aims to develop a machine learning-based Early Warning System capable of automatically detecting anomalous activities. The system is developed using the Python programming language and runs on an Ubuntu server by utilizing authentication logs and web access logs as the main data sources. The anomaly detection model is trained using normal activity data collected directly from the Ubuntu server logs to learn standard system behavior patterns. During the operational phase, the system reads server logs in real-time, extracts activity features, and analyzes them using the Isolation Forest algorithm. Activities detected as anomalies trigger alert notifications via Telegram to the administrator without performing automatic blocking. The results show that the system is able to provide early warnings for suspicious activities, thereby helping to improve server security more effectively.

The reliability of an e-commerce application is essential to ensure smooth and secure user transactions. This study discusses the implementation of Software Quality Assurance (SQA) on a web-based e-commerce application to test the functionality of the developed system. The testing methodology used in this research combines manual testing and automated testing using the Katalon Studio tool, following the Software Testing Life Cycle (STLC) framework. Manual testing was focused on validating the user interface and user experience across core workflows, including user registration, authentication, cart management, and the checkout process. Meanwhile, Katalon Studio was utilized to execute automated test scenarios on these crucial features to accelerate regression testing and ensure system stability. The results indicate that from 42 test cases executed, the SQA approach successfully identified five functional defects across three modules, categorized by severity into two High-level defects (server error on registration and missing error handling on checkout), two Medium-level defects (client-side-only address validation and cart quantity logic), and one Low-level defect (insufficient logout notification display time). Four of the five defects were resolved, raising the test pass rate from 90.5% to 97.6% during regression testing. Automated testing demonstrated a significant time efficiency of approximately 95% compared to manual execution for regression scenarios. In conclusion, the combination of manual and automated testing proved capable of thoroughly verifying software quality, ensuring that the SQA Shop application functions according to the required specifications before its release to end-users.

This research the development of a content-based website to overcome learning distractions from TikTok social media in Cuping Hamlet, Lamongan Regency. The purpose of this study was to determine the effect of TikTok social media on children's learning interest and to develop a content-based website to address learning distractions from TikTok social media in Cuping Hamlet, Lamongan Regency. The method used was a quantitative method with a questionnaire technique distributed to 30 parents of children aged 6-12 years. The results showed a significance level of <0.05, indicating a significant negative effect between TikTok social media use and children's learning interest. Furthermore, the relationship between TikTok social media and learning interest was strong and in the opposite direction, with a correlation coefficient of -0.60.. This can be interpreted that the higher the level of TikTok social media use, the lower the child's interest in learning and vice versa. Furthermore, a content-based website has been successfully developed to address learning distractions from TikTok social media. The website development used Wix which contains the home page, about, research, publications, posts (interesting learning materials and videos), and contact.

QRIS (Quick Response Code Indonesian Standard) has become a widely used national digital payment standard. User satisfaction with this service needs to be monitored continuously to ensure its sustainability. This study aims to predict the level of QRIS user satisfaction based on their experiences and perceptions expressed organically on the Twitter social media platform. The method used is sentiment analysis with the Naive Bayes classification algorithm implemented using RapidMiner software. The research data was obtained from Twitter user comments collected through web scraping techniques. The text data then went through a preprocessing stage that included cleansing, stopword filtering, stemming, and tokenizing to be prepared as features ready to be processed by the model. The data was divided into training (80%) and testing (20%) subsets for model training and validation. The results showed that the Naive Bayes model was able to predict user satisfaction sentiment with an accuracy of 80.99%. These findings indicate that the model is highly accurate in identifying satisfied comments and sufficiently sensitive in detecting dissatisfaction. This study concludes that sentiment analysis of Twitter UGC data using Naive Bayes is an effective and efficient approach for predicting QRIS user satisfaction in real time. The practical implication of this study is to provide an automatic feedback system for service providers to monitor public sentiment and take targeted corrective actions.

This research is motivated by the problems in manual attendance systems at schools, which remain vulnerable to fraud, time-consuming, and inefficient. The expected solution is to develop an automated attendance system based on face recognition that can operate in realtime with high accuracy. The research object is vocational high school students, with the applied method implementing the YOLO v10 algorithm for face detection, followed by the face_recognition library for identification. The instruments used include an Imou CCTV camera as the input device, a mid-range laptop as the hardware platform, and Python with SQLite as the software environment for data processing and attendance storage. The results show that the developed system achieved an average face detection accuracy of 96% under normal lighting and 91% under low lighting, with an average processing speed of 27 FPS. The implementation of an anti-duplication feature also ensured data validity by allowing each student to be recorded only once per day. In conclusion, the use of YOLO v10 in face-based attendance proved to be effective, efficient, and capable of reducing fraud. The implication of this study is that the system can be applied in both Islamic boarding schools and general schools as a modernization of attendance systems, with a recommendation for further development through web-based application and cloud database integration.

SR12 Herbal Cosmetics is a company engaged in the field of herbal and skin care. Founded in 2015 byToni Firmansyah, S. Farm., Apt. and Asrianty Salam, Farm. This company has a vision to provide benefits to many people through the herbal and skin care products they produce. SR12 Herbal Cosmetics products are formulated based on research from certified scientists, and have been tested at the Sucofindo Laboratory, are free of mercury and hydroquinone, and have been registered with the Indonesian Food and Drug Supervisory Agency (BPOM RI). SR12 Herbal Cosmetics has several factories in West Java Province and has an extensive distribution network with hundreds of distributors and tens of thousands of partners throughout Indonesia. The goal to be achieved is to produce a management information system model including a management information system for PT SR12 Herbal Cosmetics. The research object chosen is a company in the field of cosmetics and skin care which has its head office in Gunung Sindur, West Java. This selection aims to form a management information system design model that is able to produce relevant and timely information for planning, controlling, decision making and evaluating the performance of activities. For the Web-Based Instagram Content Management Information System Design project to Support SR12 Herbal Cosmetics' Brand Awareness, I used Agile (Scrum) due to the dynamic nature of digital marketing and potential changes to the Instagram API or business needs. This allowed SR12 to get core functionality faster and provide iterative feedback, ensuring the system built was truly relevant to their brand awareness needs.

Microplastics are extremely small plastic particles that have become a major concern in public health and environmental studies. This literature review aims to discuss the sources of microplastics, their routes of exposure to the human body, their distribution in organs, and their potential health impacts. The method used was a literature review of scientific articles and reports published from 2021 onward, retrieved from Google Scholar, PubMed, ScienceDirect, and official websites of organizations such as the WHO, OECD, and the World Bank. The review findings show that microplastics originate from plastic waste, synthetic clothing, cosmetics, vehicle tires, and food packaging. These particles have been detected in blood, lungs, the placenta, feces, and various human tissues, indicating that human exposure is widespread. However, evidence from human studies is still limited, so cause-and-effect relationships cannot yet be confirmed with certainty. Based on these findings, further research is needed to better understand the long-term health effects of microplastics. In addition, efforts to reduce single-use plastics, improve waste management systems, and increase public education are essential to reduce exposure and prevent future health risks.

One of the goals of a building is to create a comfortable environment that does not affect the health and operations of its occupants, therefore a system needs to be created to ensure comfort in classrooms. To fulfill a comfortable situation, there is a standard that regulates comfort, especially thermal and visual comfort. Thermal comfort is regulated in SNI 03-6572-2001 and visual comfort is regulated in SNI 03-6575-2001. The aim of this research is to design a tool to automatically monitor temperature and lighting, determine greater accuracy, determine temperature and lighting comfort distances, and test Smart Comfort measurement results in accordance with the SNI-03-6571-2001 and SNI-03-6575-2001 conformity standards. This design uses ESP32 with IoT-based LDR and DHT11 sensors which can be seen on the web and application, determines the accuracy and range of Smart Comfort values for monitoring temperature and lighting and determines the suitability of measurement quantities in the SDN PINANG 3 classroom.

This study aims to analyze the influence of accountability and transparency in government financial reports on the achievement of Sustainable Development Goals (SDGs) 2 in Indonesia. SDGs 2 focuses on efforts to eradicate hunger, increase food security, and improve public nutrition. The study used a quantitative approach with panel data in 34 provinces in Indonesia during the 2021–2022 period. The sampling technique was purposive sampling, resulting in a total of 68 research observations. The research data were sourced from the National Development Planning Agency (BAPPENAS), the Supreme Audit Agency (BPK), and official local government websites related to the publication of regional financial reports. The accountability variable was measured using the BPK audit opinion on the LKPD, while transparency was measured based on the openness of the publication of seven components of the regional government financial report. Data analysis was performed using the Common Effect Model (CEM) with a robust standard error approach. The results showed that accountability has a positive and significant effect on the achievement of SDGs 2 with a coefficient value of 3.919 and a significance level of 0.000. Transparency also has a positive and significant effect on the achievement of SDGs 2 with a coefficient value of 2.415 and a significance level of 0.000. In addition, accountability and transparency simultaneously proved to have a significant effect on the achievement of SDGs 2. This finding indicates that the implementation of good governance through increased accountability and transparency of financial reports can support the effectiveness of food security and sustainable development programs in Indonesia.

Early childhood education requires engaging and interactive learning media to enchance student’s motivation and participation. However, learning activities in many kindergartens are still dominated by conventional methods, which are less effective in attracting children’s attention. This study aims to design and implement a web-based interactive educational game as an alternative learning medium for early childhood education. This research applies the ADDIE development model, consisting of analysis, design, development, implementation, and evaluation stages. Data were collected through observation, questionnaires, and literature review to identify user needs and evaluate the system. The educational game was developed using web-based technologies, enabling easy access through a browser without additional installation. The results show that the developed educational game improves children’s learning interest and engagement during the learning process. The system is also considered user-friendly and suitable for early childhood characteristics, both in terms of interface design and interactivity. Therefore, the web-based educational game is feasible and effective as an alternative learning medium to support early childhood education.

Public services are one of the essential functions of village-level government as they are directly related to the needs of the community. However, in Pontap Village, Palopo City, service processes are still carried out manually, which often leads to obstacles such as service delays, difficulties in record-keeping, and limited access to information for residents. This study aims to design and develop a web-based public service information system to improve the efficiency and quality of services at the village office. The system was developed using the Waterfall method, which consists of requirement analysis, system design, implementation, testing, and maintenance stages. The system was built using the PHP programming language with the Laravel framework and utilizes MySQL as the database which is managed using HeidiSQL. System modeling was carried out using use case diagrams and activity diagrams, while testing was conducted using the black-box testing approach to ensure that all functions operate according to specifications. The resulting system provides community complaint services, administrative letter services, and information on health service schedules such as posyandu and puskesmas activities. It is expected that this system will facilitate residents in accessing information, accelerate service processes, and improve data accuracy through an integrated digital platform. This research is expected to serve as a solution to support the digitalization of public services in Pontap Village and to become a reference for the development of similar systems in other regions.

Currently, the management of the damaged goods reporting at the Class 1A Jambi District Court still relies on manual procedures through verbal communication and physical logbooks. This mechanism is prone to recording errors, risks of document loss, and complicates real-time monitoring of repair statuses. This study aims to design a web-based Damaged Goods Reporting Information System to improve the effectiveness, transparency, and efficiency of internal asset management. The research method employs a qualitative approach with data collection techniques consisting of interviews, observations, and documentation. System development implements the Waterfall model, comprising requirement analysis, design, implementation, and testing phases. The result of the study deliver a web-based application that integrates features for report input, proof of damage photo uploads, admin validation, and real-time monitoring of repair status. This system successfully simplifies bureaucratic workflows, accelerates response times for damage handling, and minimizes administrative errors.

The process of creating and verifying employee ID cards at BKPSDMD Jambi City was previously carried out manually, resulting in lengthy processing times, data entry errors, and a high risk of identity forgery. This study aims to design and implement a web-based employee ID card digitalization system integrated with QR Code technology to improve the efficiency, accuracy, and security of employee identity verification. The system was developed using the Waterfall methodology, consisting of requirements analysis, system design, implementation, testing, and maintenance. The application was built using Native PHP, MySQL, HTML, CSS, and JavaScript. Functional testing was conducted using Black Box Testing with 12 test scenarios, while usability evaluation employed the System Usability Scale (SUS) involving 20 respondents. The results indicate that all core system features functioned properly, achieving a 100% success rate on valid test scenarios. Furthermore, the usability evaluation produced an average SUS score of 71.75, which falls into the good and acceptable categories. The implementation successfully accelerated the ID card issuance process, improved data management accuracy, and enhanced identity verification security through QR Code integration directly connected to the employee database. Therefore, the developed system effectively supports digital transformation and improves the efficiency of employee identity management at BKPSDMD Jambi City.

Unpredictable changes in weather conditions have increased the need for real-time weather monitoring systems. This study aims to implement an Internet of Things (IoT)-based adaptive weather monitoring and alarm system by utilizing JSON Web API as a weather data source. This system is built using NodeMCU ESP8266 as the main microcontroller connected to the OpenWeatherMap API service via an internet network. The weather data obtained includes temperature, humidity, and weather conditions which are then displayed on the MAX7219 Matrix monitoring and display website in real-time. In addition, this system is equipped with an adaptive alarm feature that can be controlled through the website so that users can set alarms according to their needs. The research method used is an experimental method with a descriptive approach through the stages of system design, hardware and software implementation, and system testing. Based on the test results, the system successfully displays weather information in real-time and runs automatic alarms according to user settings. With this system, users can obtain weather information and time reminders more effectively, practically, and efficiently.

Reproductive health is an aspect of health that still requires serious attention, particularly for women of reproductive age. Polycystic Ovary Syndrome (PCOS) is a hormonal disorder with a prevalence of 3.4% among women worldwide, yet it often goes undetected due to a lack of awareness. This community service activity aims to increase the knowledge of women of reproductive age regarding menstruation, PCOS, and the importance of early detection through an educational webinar titled “Hormone Talk: Exploring Menstruation, PCOS, and the Importance of Early Detection.” The event was held online via the Zoom Meeting platform on December 13, 2025, and was attended by over 100 participants, the majority of whom were female students. The evaluation method utilized pre-tests and post-tests analyzed using a Dependent T-test. The results showed a significant increase in the average knowledge score from 64.78 (pre-test) to 79.67 (post-test), with a difference of 14.89 points and a p-value of 0.000. This demonstrates that reproductive health educational webinars are effective in enhancing participants’ knowledge. It is hoped that this activity can serve as a model for sustainable digital-based health promotion interventions in efforts to improve reproductive health literacy among Indonesian women.

Soybean is an important food commodity in Indonesia because it is the main raw material for tofu and tempeh, two major protein sources widely consumed by the population. However, domestic soybean production remains far below national demand resulting in heavy dependence on imports. In contrast maize is increasingly preferred by farmers due to its higher productivity and a more stable economic value. Therefore, maize–soybean intercropping has emerged as a promising strategy to improve land-use efficiency while increasing soybean production without reducing maize cultivation. This study systematically mapped and synthesized maize–soybean intercropping research in Indonesia and conducted a meta-analysis of Land Equivalent Ratio LER values reported across studies. Literature searches using Scopus, Web of Science, and Google Scholar identified 179 eligible publications published between 1978 and 2023. Most studies focused on agronomic factors such as variety selection spacing arrangement and fertilizer management. Meta-analysis showed average LER values of 1.47 ± 0.046 for maize–soybean intercropping and 1.36 ± 0.081 for maize–mung bean intercropping indicating advantages over monoculture systems. However, inconsistencies in methodology and reporting standards limited study comparability and sustainability assessments. Future research should integrate ecological, social, and long-term economic indicators alongside standardized reporting frameworks to strengthen evidence-based intercropping recommendations nationally for sustainable agriculture.