This study aims to develop a robust prioritization model for municipal projects in the Holy Metropolitan Municipality (Makkah) to address the challenges of aligning short-term and long-term objectives. The research explores How multi-criteria decision-making (MCDM) techniques can prioritize municipal projects effectively while ensuring alignment with strategic goals and local needs. The methodology employs the analytic hierarchy process (AHP) and exploratory factor analysis (EFA) to ensure methodological rigor and data adequacy. Data were collected from key stakeholders, including municipal planners and community representatives, to enhance transparency and reliability. The model’s validity was assessed through latent factor analysis, confirming the relevance of identified criteria and factors. Results indicate that flood prevention projects are the highest priority (0.4246), followed by road projects (0.3532), park construction (0.1026), utility projects (0.0776), and digital transformation (0.0416). The study highlights that certain factors are critical for evaluating and prioritizing municipal projects. “Capacity and Demand” emerged as the most influential factor (0.5643), followed by “Strategic Alignment” (0.2013), “Project Interdependence” (0.1088), “Increasing Investment” (0.0950), and “Risk” (0.0306). These findings are significant as they offer a structured, data-driven approach to decision-making aligned with Saudi Vision 2030. The proposed model optimizes resource allocation and project selection, representing a pioneering effort to develop the first prioritization framework specifically tailored to Makkah’s unique municipal needs. Notably, this is the first study to establish a prioritization method specifically for Makkah’s municipal projects, providing valuable contributions to the field.

Fujian Tubao, a defensive residential structure predominantly found in central Fujian, represents a significant cultural heritage of the region. However, with the rapid urbanization underway, Fujian Tubao faces the threat of extinction, presenting severe challenges to its survival and development. Identifying a sustainable development path for Fujian Tubao is crucial for preserving regional culture. This study uses Fuxing Bao, a quintessential example of Fujian Tubao, as a case study to explore conservation methods based on adaptive reuse. Through field surveys, questionnaires, in-depth interviews, and case studies, we analyze the historical background of the building, focusing on the current physical and social environment of Fuxing Bao. Our findings indicate that the current state of preservation of Fuxing Bao can meet the requirements for adaptive reuse. By integrating results from surveys and interviews with local villagers, we propose sustainable development strategies and conservation methods. This research offers a sustainable development model for Fujian Tubao and other traditional regional dwellings. By adopting an adaptive reuse perspective, it aims to better address the conflict between modern living and traditional architectural preservation, ensuring that these architectural spaces are properly protected and continue to play a unique role in contemporary society.

This research aims to develop a Synergy Learning Model in the context of science learning.  This research was conducted at Islamic Junior High School, Madrasah Tsanawiyah Negeri 2 Medan, involving 64 students of Grade 7 as the research subject. The method used in this research refers to the development research approach (R&D). In collecting the data, the research employed test and non-test techniques. The results prove that the Synergy learning model developed is effective in improving student learning outcomes. This is evident through the t-test statistical test where the t-count of 4.26 is higher than the t-table of 1.99. In addition, the level of practicality with a score of 3.39 is categorized as practical. This learning model emphasizes the learning process that supports the development of science skills and develops students' competencies in planning, collaborating, and critically reflecting. The findings of this study contribute to pedagogical practices and literature in the field of science learning.

The purpose of this study was to examine the effect of E-integrated marketing communication on consumers’ purchasing behavior of mobile services. The population for the study involves all orange telecom mobile service customers in Jordan. Three hundred ninety-five questionnaires were distributed to orange telecom customers in Jordan, however, 375 only returned, which has been used for analysis. structural equation modeling using programs such as AMOS was used to investigate the impact of E-integrated marketing communication on consumers’ purchasing behavior. Data was collected through questionnaires was sent to study sample. The results of the study showed that E-integrated marketing communication had a positive impact on consumers’ purchasing behavior. Based on the findings, the study recommended that Orange Telecom should focus more on e-public relations to create a favorable image of the company among different groups of consumers, which can potentially enhance their purchasing behavior towards its mobile services. It is imperative for Orange Telecom to prioritize its e-integrated marketing communication strategy to effectively reach out to its target audience and influence their purchase decisions.

Accurate demand forecasting is key for companies to optimize inventory management and satisfy customer demand efficiently. This paper aims to Investigate on the application of generative AI models in demand forecasting. Two models were used: Long Short-Term Memory (LSTM) networks and Variational Autoencoder (VAE), and results were compared to select the optimal model in terms of performance and forecasting accuracy. The difference of actual and predicted demand values also ascertain LSTM’s ability to identify latent features and basic trends in the data. Further, some of the research works were focused on computational efficiency and scalability of the proposed methods for providing the guidelines to the companies for the implementation of the complicated techniques in demand forecasting. Based on these results, LSTM networks have a promising application in enhancing the demand forecasting and consequently helpful for the decision-making process regarding inventory control and other resource allocation.

This study aims to explore the link and match policy through industrial classes and its impact on the competence and employability of Vocational High School (VHS) graduates. The importance of this research is to address the gap between education and industry by assessing the effectiveness of industrial classes in improving the skills and employability of VHS graduates. Horison Industrial Class (HIC) in 4 schools, namely: (1) SMKN 57 Jakarta, 2 batches of Hospitality expertise programs; (2) SMKN 6 Yogyakarta, there are 3 batches of Hospitality expertise programs; (3) SMKN 6 Semarang, there are 2 batches of Hospitality expertise programs; (4) SMKN 2 Semarang. This research emphasizes the important role of industry involvement and commitment in aligning the curriculum with industry needs. The field findings show that the implementation of the link and match policy through industrial classes significantly affects the quality of learning in VHS. The study also highlights the influence of government support and industry associations in ensuring the successful implementation of industrial classes. Student participation in industry classes directly enriches their learning experiences by allowing them to engage in direct practice in a real work environment. These findings can contribute to the implementation of policies and regulations in the field of education, especially in the context of vocational education. The findings of this study can also be applied to vocational students to improve the quality of graduates in order to meet the qualification standards of employees in companies or industries.