This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.
This study explored the relationships between college students’ indecisiveness, anxiety, and career decision-making ability. Using the convenience sampling method, 1072 college students at a college in Hunan Province, China completed a questionnaire online that included the Indecisiveness Scale, Career Exploration and Decision Self-Efficacy Scale, and Generalized Anxiety Scale-7. Participants reported their gender and place of origin (rural or city). They indicated whether they were an only child, were left behind, and liked the major they were studying. The t-test was used to identify differences in indecisiveness, career decision-making ability, and anxiety according to demographic characteristics. Correlations were calculated between the main variables of interest. Regression analysis was conducted to test the mediation model. Participants who liked their major were significantly more indecisive than those who did not like their major. Career decision-making ability was significantly higher among men than women, participants from urban areas than those from rural areas, participants who were an only child than those with siblings, and among non-left-behind participants than those who were left behind. Anxiety was significantly lower in participants who liked their major than those who did not like their major. In addition, anxiety partially mediated the relationship between indecisiveness and career decision-making ability. College students’ indecisiveness and career decision-making ability are affected by sociocultural background, gender, family background, and career interest. Anxiety partially mediates the relationship between indecisiveness and career decision-making ability. Implications of the findings for counseling college students are discussed.
Uncontrolled economic development often leads to land degradation, a decline in ecosystem services, and negative impacts on community welfare. This study employs water yield (WY) modeling as a method for environmental management, aiming to provide a comprehensive understanding of the relationship between Land Use Land Cover (LULC), Land Use Intensity (LUI), and WY to support sustainable natural resource management in the Cisadane Watershed, Indonesia. The objectives include: (1) analyzing changes in WY for 2010, 2015, and 2021; (2) predicting WY for 2030 and 2050 under two scenarios—Business as Usual (BAU) and Protected Forest Area (PFA); (3) assessing the impacts of LULC and climate change on WY; and (4) exploring the relationship between LUI and WY. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model calculates actual and predicted WY conditions, while the Coupling Coordination Degree (CCD) analyzes the LULC-WY relationship. Results indicate that the annual WY in 2021 was 215.8 × 108 m³, reflecting a 30.42% increase from 2010. Predictions show an increasing trend in WY under both scenarios for 2030 and 2050 with different magnitudes. Rainfall contributes 88.99% more dominantly to WY than LULC. Additionally, around 50% of districts exhibited unbalanced coordination between LUI and WY in 2010 and 2020. This study reveals the importance of ESs in sustainable watershed management amidst increasing demand for natural resources due to population growth.
This study aims to identify and the implementation of ASN Management policies on career development aspects based on the merit system in the West Java Provincial Government and 6 Regency/City Governments in West Java Province. The failure of the institutionalization of the meritocratic system in ASN career development is partly triggered by the symptoms of the appointment or selection of officials in the central and regional levels not based on their professionalism or competence except for subjective considerations, political ties, close relationships and even bribery. This study uses a qualitative method with a descriptive approach. The operationalization concept in this study uses Merilee S. Grindle’s Policy Implementation theory which consists of dimensions of policy content and its implementation context. The factors that cause the implementation of the policy to be less than optimal include: 1. Uneven understanding of meritocracy; 2. Slowness/unpreparedness in synchronizing central and regional rules/policies; 3. The information integration system between the center and regions has not yet been implemented; 4. Limited supporting infrastructure; 5. Limited permits for related officials; 6. Transparency; 7. Collaboration across units/agencies; 8. External intervention; 9. Use of information systems/technology. To optimize these factors, an Accelerator of Governmental Unit’s Success (AGUS) model was created, which is a development of the Grindle policy implementation model with the novelty of adding things that influence implementation, including top leader’s commitment and wisdom, effectiveness of talent placement, on-point human development, technology savvy, cross-unit/agency collaboration, and monitoring and evaluation processes.
The article highlights Malaysia’s multicultural history, the advancement of Internet technology, and the worldwide appeal of Chinese food, all of which serve as a good basis for the project. This study focuses on Malaysian Chinese takeout systems. The research’s primary goals include developing new business options for the Chinese food sector, as well as enhancing customer happiness and efficiency of takeout systems. As a result, the project intended to create a Web-based system for managing several tasks associated with meal ordering by users. For the system development, an Object-Oriented System Development (OOSD) methodology was used, mostly with the Java programming language. Model-View-Control (MVC) framework was employed throughout development to improve system administration. Redis and HTTP session technologies were included for user login to increase system security. For database operations, MyBatis and MyBatis Plus were also employed to enhance ease and security. The system adheres to design principles and leverages technologies like ElementUI and jQuery to further fulfill this criterion to provide a user-friendly interface. The results of this study demonstrate significant improvements in the overall efficiency of the takeout process, leading to enhanced user experiences and greater customer satisfaction. In addition to streamlining operations, the system opens new avenues for the Malaysian Chinese food industry to capitalize on the growing demand for online food ordering. This research provides a solid foundation for future innovations in takeout systems and serves as a reference point for enhancing the Chinese gastronomy sector in a rapidly digitizing world.
Water scarcity, particularly in arid and semi-arid regions, is a critical issue affecting forest management. This study investigates the effects of drought stress on the water requirement and morphological characteristics of two important tree species Turkish pine and Chinaberry. Using a factorial design, the study examines the impact of three age stages (one-year-old, three-year-old, and five-year-old plants) and three levels of drought stress on these species. Microlysimeters of varying sizes were employed to simulate different drought conditions. Soil moisture was monitored to show the effect of the various irrigation schedules. The study also calculated reference crop evapotranspiration (ET0) using the PMF-56 method and developed plant coefficients (Kc) for the species. Results showed that evapotranspiration increased with soil moisture, peaking during summer and decreasing in winter. Turkish pine exhibited higher plant ET than Chinaberry, particularly among one-year-old seedlings. Drought stress significantly reduced evapotranspiration and water uses for both species, highlighting the importance of efficient water management in afforestation projects. The findings underscore the necessity of selecting drought-resistant species and optimizing irrigation practices to enhance the sustainability of green spaces in arid regions. These insights are crucial for improving urban forestry management and mitigating the impacts of water scarcity in Iran and similar climates globally.
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