Innovation can be applied in every aspect of life. Similarly, innovation can support the implementation of an accountable education system and support regional competitiveness. Innovation is easy to echo, but difficult to implement. Especially with regard to the Education curriculum which is based on many teaching norms. For this reason, the independent curriculum is a bridge for students and teachers in pouring their innovative ideas through projects that link and match with the world of Education. The problem is that not all schools in Boyolali Regency dare to experiment. There are only 20 schools that seem to be making innovations from the total number of schools as many as ± 400 school units. Qualitative descriptive study method with analysis through problem trees. The result of the study is that an innovation model will be created three concepts, namely Training model, professional Development and Capability Development using problem-based learning methods, project-based learning and discovery learning.
To address the escalating online romance scams within telecom fraud, we developed an Adaptive Random Forest Light Gradient Boosting (ARFLGB)-XGBoost early warning system. Our method involves compiling detailed Online Romance Scams (ORS) incident data into a 24-variable dataset, categorized to analyze feature importance with Random Forest and LightGBM models. An innovative adaptive algorithm, the Adaptive Random Forest Light Gradient Boosting, optimizes these features for integration with XGBoost, enhancing early Online romance scams threat detection. Our model showed significant performance improvements over traditional models, with accuracy gains of 3.9%, a 12.5% increase in precision, recall improvement by 5%, an F1 score increase by 5.6%, and a 5.2% increase in Area Under the Curve (AUC). This research highlights the essential role of advanced fraud detection in preserving communication network integrity, contributing to a stable economy and public safety, with implications for policymakers and industry in advancing secure communication infrastructure.
Terms and Conditions are always encountered when using social media applications to determine which data can be accessed and what cannot. However, there are shortcomings in their implementation and communication, often causing users to be unwilling to read them. Therefore, this study aimed to analyze the effectiveness of implementing partial consent in Terms and Conditions concerning user Data Awareness and Data Security in social media. This Paper administered a questionnaire, distributed with a form, to students who use social media to understand their opinions regarding the partial consent concept. This paper analyzed the data using descriptive statistical methods. The results show a positive response from respondents towards implementing the partial consent concept, the users feel the terms and conditions are more effective in increasing user data awareness and security.
The digital era has transformed education, making digital literacy essential for teachers to integrate technology and enhance student outcomes effectively. This study aims to examine how school culture influences teachers’ performance through their digital literacy, focusing on junior high school teachers in Malang City, East Java, Indonesia. Employing a quantitative approach, data were collected from 214 teachers out of a 457 population using questionnaires. The analysis was conducted through AMOS for Confirmatory Factor Analysis (CFA), SPSS for descriptive statistics, and PLS-SEM for hypothesis testing. The findings reveal that school culture significantly affects teachers’ digital literacy (Ho1) and teacher performance (Ho2) with supportive and innovative environments, while rigid cultures limit creativity. Furthermore, digital literacy was found to enhance teachers’ performance (Ho3) and mediate the impact of school culture on teachers’ performance (Ho4), enhancing teachers’ effectiveness in planning, implementing, and evaluating instruction. This study highlights the critical role of school culture in shaping digital literacy and offers new insights for improving teacher practices in diverse educational settings. Moreover, the role of education policies in fostering a collaborative school culture that enhances teachers’ digital literacy and performance, leading to improved educational outcomes, plays a crucial implication.
This study aims to examine the influence of employee and entrepreneur competencies on work efficiency and performance of export companies at the Nong Khai border checkpoint. The research conducted is a quantitative survey. The population for this study includes employees and entrepreneurs from the cross-border export service industry, exporters, and freight forwarder agents operating at the Nong Khai border checkpoint. A non-probability sampling method was employed to select participants. The sample size was Cochran estimated using Cochran’s formula. A structured questionnaire was used to collect data from 385 logistics employees and entrepreneurs selected through purposive sampling. The questionnaires were distributed to employees and entrepreneurs from the export entrepreneurial industry, cross-border export service providers, exporters, and freight forwarder agents at the Nong Khai border checkpoint. The findings revealed that employee and entrepreneur competencies have a direct influence on the work efficiency and performance of export companies. The study concludes that enhancing the competencies of employees and entrepreneurs positively impacts work efficiency and the overall export performance of the company. The research suggests that entrepreneurs should prioritize training and competency development for employees to further improve work efficiency.
Adequate sanitation is crucial for human health and well-being, yet billions worldwide lack access to basic facilities. This comprehensive review examines the emerging field of intelligent sanitation systems, which leverage Internet of Things (IoT) and advanced Artificial Intelligence (AI) technologies to address global sanitation challenges. The existing intelligent sanitation systems and applications is still in their early stages, marked by inconsistencies and gaps. The paper consolidates fragmented research from both academic and industrial perspectives based on PRISMA protocol, exploring the historical development, current state, and future potential of intelligent sanitation solutions. The assessment of existing intelligent sanitation systems focuses on system detection, health monitoring, and AI enhancement. The paper examines how IoT-enabled data collection and AI-driven analytics can optimize sanitation facility performance, predict system failures, detect health risks, and inform decision-making for sanitation improvements. By synthesizing existing research, identifying knowledge gaps, and discussing opportunities and challenges, this review provides valuable insights for practitioners, academics, engineers, policymakers, and other stakeholders. It offers a foundation for understanding how advanced IoT and AI techniques can enhance the efficiency, sustainability, and safety of the sanitation industry.
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