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The growth of information technology has driven changes in consumer behavior, one of which is through e-commerce platforms such as Shopee. This phenomenon has generated a large number of customer reviews, including those for local cosmetic products such as Wardah. These reviews serve as an important source of information for understanding customer perceptions and satisfaction levels. However, manual analysis of large and linguistically diverse datasets is inefficient and potentially subjective. This study aims to implement the multi-category Naive Bayes algorithm to classify the sentiment of Wardah product reviews on Shopee into three categories: positive, negative, and neutral. The data were collected using a web scraping technique and processed through a series of preprocessing stages including case folding, tokenization, stopword removal, stemming, and text cleaning. Subsequently, term weighting was performed using the TF-IDF method prior to classification. Model performance was evaluated using a confusion matrix as well as accuracy, precision, and recall metrics. The results indicate that the multi-category Naive Bayes algorithm achieved an accuracy of 86.00%, a precision of 86.63%, and a recall of 98.24%. This approach can assist business practitioners in objectively understanding customer opinions and support decision-making in business strategy and product development.

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.

This study discusses a student concentration detection system using Convolutional Neural Network (CNN) with the MobileNetV2 architecture. The dataset was adapted from Classroom Student Behaviors and mapped into four concentration categories: highly focused, focused, less focused, and unfocused. The system was tested with a 720p webcam and produced real-time detection data. The evaluation results show an overall accuracy of 75.85%, with the highest precision achieved in the focused class (0.9859) and the highest recall in the highly focused (0.9739) and unfocused (0.9811) classes. The confusion matrix indicates that the focused class was detected most consistently, while highly focused and unfocused classes were often misclassified as focused, resulting in lower precision. In real-time testing, the system operated at an average of 7 FPS and worked optimally when students faced the camera directly with sufficient lighting, but its performance decreased significantly at face angles greater than 45°. User evaluation shows that 75% of students rated the detection results as accurate/very accurate with an average satisfaction score of 3.6 out of 5, and 75% felt assisted in recognizing their concentration level. From the teachers’ perspective, most stated that the results were consistent with classroom observations, and all expressed willingness to reuse the system.

This study aims to analyze public sentiment toward the hashtag #KaburAjaDulu, which has circulated widely on the social media platform X (formerly Twitter). The hashtag reflects the growing anxiety among the public, especially younger generations, regarding socio-political issues in Indonesia. The data were collected using web scraping techniques, focusing on user-generated tweets that contain the hashtag. A comprehensive text preprocessing phase was conducted to clean the raw data by removing irrelevant elements such as URLs, emojis, numbers, and punctuation. The research applies a hybrid classification approach using a combination of Support Vector Machine (SVM) and Random Forest algorithms to categorize sentiment into three classes: positive, negative, and neutral. The performance of the model was evaluated using metrics such as accuracy, precision, recall, and F1-score to determine the effectiveness of the classification. The study aims to demonstrate that combining algorithms can improve classification performance compared to using a single algorithm. This research contributes to the field of sentiment analysis and provides valuable insights for researchers, policymakers, and social observers in understanding public opinion trends in digital media.

In the current era of digital transformation, higher education institutions face increasing pressure to manage their reputation strategically through digital communication channels. This study investigates the relationship between digital communication strategies employed by higher education institutions and their perceived reputation among students and surrounding communities. Employing a mixed-methods approach combining quantitative survey with 320 respondents (220 students and 100 community members) and qualitative in-depth interviews with 18 informants from three universities in Bandung, West Java, Indonesia, this research examines how social media management, website quality, digital content consistency, and online engagement practices influence institutional reputation. The findings reveal that digital communication strategy has a significant positive effect on higher education reputation (r = 0.724, p < 0.01), with social media engagement and content consistency emerging as the most influential dimensions. Community respondents demonstrated higher sensitivity to Corporate Social Responsibility (CSR) content compared to students, who prioritized academic information quality and responsiveness. This study contributes theoretically to the application of Agenda-Setting Theory and Stakeholder Theory in the digital context of higher education and provides practical recommendations for university communication offices in developing more effective digital strategies to build and maintain institutional reputation.

Computers in one of the network companies at PT. Estrada uses the Fortinet operating system. The final result expected through this implementation is to comprehensively see the capabilities of the firewall on Fortinet in overcoming the problem of blocking social media applications and streaming platforms during working hours. Blocking the application in question is the ability to filter web processes such as Facebook, Instagram, YouTube, etc. In the tests carried out, web filtering was able to block applications on social media and streaming platforms, which proves that the performance of web filtering is quite good. In analyzing web filtering performance, use the office hour rule tool by carrying out the rule schedule in the Fortinet network and displaying all the information in detail. The final result obtained in the network application filtering simulation process using Fortinet is that every network sent cannot be entered (blocked) on both social media applications and streaming platforms.

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.

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.

Librarians, as information specialists, play a vital role in managing and providing access to digital libraries. Despite the availability of digital information through repositories and digital libraries, a gap remains between users and their effective utilization. This underscores the importance of librarians in facilitating access and supporting users. This study analyzes the role, competencies, and challenges faced by librarians at the UPA Library of the University of Bengkulu in the digital knowledge ecosystem. A qualitative descriptive approach was used, with data collected through semi-structured interviews with four librarians and two users, direct observation, and documentation. Data were analyzed using data reduction, presentation, and conclusion drawing. The findings show that librarians act as information specialists by providing access through the OPAC system, repositories, digital libraries, e-journals, Springer Digital References, Instagram, and the library website. They evaluate and ensure credible digital information sources, preserve and back up collections, and assist users in information searches. However, librarians face challenges such as budget constraints, low user awareness, limited human resources, network issues, restricted access, and inadequate collections. These findings contribute to understanding the role of librarians as information specialists.

This study aims to examine the role of customer trust as a mediating variable in the relationship between digital marketing strategies and consumer behavior. As digital marketing evolves, companies are required not only to create engaging content but also to build strong trust to influence purchase intention, loyalty, and customer engagement. This research employs a systematic literature review (SLR) following PRISMA guidelines, selecting 52 empirical articles from reputable international databases such as Scopus, Web of Science, EBSCOhost, and ScienceDirect, published between 2015 and 2026. The analysis involved thematic and descriptive synthesis to assess the strength of digital marketing’s impact on customer trust and consumer behavior outcomes. The results indicate that digital marketing has a significant positive effect on customer trust formation (β=0.652; p<0.001). Customer trust functions as a partial mediator that strengthens the impact of digital marketing on purchase intention, loyalty, and engagement. The direct effect of digital marketing on consumer behavior is weaker when trust is not optimally established. These findings emphasize that effective digital marketing strategies must focus on transparency, security, credibility, and personalization to maximize consumer behavior outcomes. Practically, this study provides important implications for companies and digital marketing practitioners, highlighting that successful campaigns rely not only on content and visibility but also on the ability to build customer trust. The study also opens avenues for future research to examine more specific trust dimensions, including platform integrity, information quality, and social proof, within increasingly complex digital marketing contexts.

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.

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.

This research aims to develop a web-based Attendance Monitoring System for CPNS Latsar Training Participants using the Laravel and Filament framework at the University of Jambi. The research method used is Research and Development (R&D) with the Software Development Life Cycle (SDLC) Waterfall model, which includes the stages of needs analysis, design, Implementation, Testing, and Maintenance of the system. The results of the study show that the system successfully runs digital attendance features, real-time monitoring, and generates automatic reports with a test success rate of 100%. In addition, the results of the User Acceptance Testing (UAT) obtained a feasibility score of 92.8% in the category of "Very Feasible". These findings confirm that the developed system is able to help the attendance administration process, improve the ease of monitoring participants, and support the management of attendance data in a more structured and efficient manner. Thus, this web-based monitoring system can be an innovative solution in supporting the effectiveness of the Implementation of CPNS Latsar Training within the University of Jambi.

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.

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.

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.

The increasing use of web applications in various sectors has made security a major concern due to the high risk of attacks targeting the application layer. This study aims to analyze the effectiveness of the F5 Web Application Firewall (F5 WAF) in mitigating vulnerabilities in the OWASP Juice Shop application. Testing was conducted using 10 attack scenarios including SQL Injection, Cross-Site Scripting (XSS), Insecure Direct Object Reference (IDOR), and Information Disclosure before and after F5 WAF implementation. The test results showed that all tested attack scenarios were successfully mitigated after F5 WAF implementation. These findings indicate that the F5 WAF is able to provide effective protection against various vulnerabilities at the application layer and improve the security of web applications in the test environment used.

This study aims to formulate an information system strategic planning model for PT Athria Cipta Mandiri using the Ward and Peppard method. The research was conducted because the company still faces several problems in managing tender and construction project data, such as unintegrated systems between divisions, semi-digital administrative processes, repeated data input, the absence of a centralized database, and project reporting that has not been carried out in real time. This study uses a qualitative descriptive approach with data collection techniques through observation, interviews, and literature study. The analysis was conducted using Value Chain, PESTEL, SWOT, Critical Success Factor, McFarlan Strategic Grid, and application portfolio recommendations. The results show that PT Athria Cipta Mandiri needs an integrated information system for tender and project management, web-based project reporting and monitoring, a document management system, business intelligence dashboard, centralized cloud database, and stronger IT governance. The proposed strategy is expected to improve operational efficiency, data accuracy, inter-division coordination, and data-based managerial decision making.

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.