The accelerating integration of artificial intelligence (AI) within the field of integrated marketing has prompted a reevaluation of the competencies required of future creative professionals. This study examines the preparedness of multimedia art students in the Philippines to engage with AIenhanced marketing environments. Anchored in the TaskTechnology Fit (TTF) Model, the research investigates students' familiarity with and attitudes toward key AI applications, including automated audience targeting, personalized content delivery, and real-time campaign optimization. The findings indicate a growing awareness of AI's relevance; however, this is accompanied by critical gaps in training access, institutional infrastructure, and ethical literacy-particularly in areas concerning data privacy and algorithmic fairness. While respondents exhibit cautious optimism regarding AI's capacity to augment creative and strategic functions, the study underscores the urgent need for curriculum development, crosssector collaboration, and ethical guidelines to support humanAI collaboration. These efforts are essential to cultivating a resilient, future-ready marketing workforce capable of navigating the evolving dynamics of AI-driven industries.

Generative AI is transforming digital creation by providing artists with tools that enhance efficiency and unlock new creative possibilities. In multimedia arts, including the growing digital art scene in the Philippines, AI-powered platforms are being used to accelerate workflows, automate tasks, and introduce innovative artistic techniques. While these advancements enable Filipino digital creators to experiment and increase productivity, they also raise concerns about originality, authenticity, and the diminishing value of traditional artistic skills. This study examines student perspectives on AI's impact using aspect-based sentiment analysis. The findings reveal that while students appreciate AI's accessibility and time-saving benefits, many remain cautious about its long-term influence on artistic growth. The Diffusion of Innovations Theory was applied to analyze AI adoption, highlighting both its advantages and challenges. Ethical concerns, such as copyright issues, fair attribution, and the potential devaluation of human-created art, continue to spark debate. These results emphasize the importance of an educational approach that integrates AI as a supportive tool rather than a replacement for human creativity. For Filipino digital creators, especially those in animation, graphic design, and content creation, it is crucial to balance AI's advantages with a strong foundation in artistic expression. Future studies should explore how AI can be leveraged to empower artists while preserving the unique cultural and creative identity of Filipino multimedia arts.

The world is rapidly changing and experiencing a rapid increase in population, especially in cities and urban areas. The growth in population in these urban areas results in a need for a more competitive and sustainable system. In the onset of the fourth industrial revolution, the trend in equipping these cities with advanced mechanisms in improving the quality of life and service in these cities is needed. In this study, a neural network - based approach for factor prioritization was implemented to determine the most influential factor in the smart city (SC) development implementation in the Philippines. Using the neural network internal characteristics including the Levenberg-Marquardt (LM) as the training algorithm (TA) and the hyperbolic tangent sigmoid (HTS) as the transfer function (TF). The study utilized the 18-37-1 network structure for the neural network model with an R value of 0.95003 and MSE of 0.032609. The connection weights (CW) from this network were utilized to calculate the relative importance (RI) of the factors affecting the smart city implementation through Garson's Algorithm (GA). The results of the study revealed that the most influential parameter (MIP) to the smart city implementation is the SCPD2 - analyzing solutions fit with strategic objectives. Moreover, the results and findings of the study could assist the city planners and SC strategy development authorities in the integration of different systems in the SC implementation.

As part of economic progress, there has been a surge in construction projects in the past few years. It is known that construction has negative and detrimental effects on the environment. The use of sustainable practices needs to be integrated into the construction processes to minimize these negative impacts. This paper introduces a prioritization method for determining the most influential factor to the implementation of environmental smart guidelines for sustaining environmentally friendly programs using sensitivity index (SI) method. Several areas were considered in this study including environmental, ecological, social, and economic impacts. Using the backpropagation-neural network (BPNN) modeling, four models for environmental, ecological, social, and economic impact ratings were developed with 15-31-1, 4-9-1, 9-19-1, and 2-5-1 network topologies (input neuron-hidden neuron-output neuron) for environmental, ecological, social, and economic impact rating, respectively. The R values for the models were observed to range from 0.97652 to 0.99901. To determine the trend of the impact of the subsets of each areas, sensitivity index method was used and the findings revealed that the water pollution reduction in the project is the most influential subset to the environmental impact rating, presence of planting area in the project for the ecological impact rating, fair sharing of benefits of the project for the social impact rating, and self-liquidation capacity of the project for the economic impact rating. The results of the study could assist managers and planners in addressing key areas and concerns in the effective implementation of smart and sustainable practices in projects.

The adoption of information technology in healthcare has resulted in novel solutions for improving patient care and operational efficiency. This study details the design and implementation of a web-based clinic management system augmented with sentiment analysis to evaluate and enhance patient satisfaction. The system utilizes natural language processing and machine learning to autonomously assess patient feedback, understanding feelings (negative, positive, and neutral) regarding critical aspects such as waiting times, doctor-patient interactions, care efficacy, and overall clinic experience. The system underwent alpha and beta testing, commencing with controlled trials and then involving real-world evaluations with clinic attendants, physicians, and patients. An evaluation conducted in a dermatology clinic revealed the system's effectiveness in detecting service deficiencies and informing enhancements. Thus, this study suggests that the integration of sentiment analysis in clinical management systems enhances data-driven decision-making, hence improving patient experiences and optimizing operations.

Loan management in transportation cooperatives involves the assessment, approval, disbursal, and monitoring of loans for various member needs, ensuring compliance with regulations, and providing support throughout the loan lifecycle. The traditional manual processes and paperwork used in loan management are prone to errors and data redundancy, are time-consuming and inefficient, lack transparency, and cause difficulty in data analysis and reporting, highlighting the need for a proficient Loan Management Website and Mobile Application. This study presents the development of a comprehensive system that efficiently handles data, integrates the credit scoring system, and leverages the FICO score for accurate loan amount recommendations, enhancing decision-making and enabling improved money monitoring, risk management, and record storage. The system's quality was evaluated using ISO 9126's software characteristics such as functionality, usability, reliability, and portability, yielding an overall mean score of 4.71 for the web application and 4.68 for the mobile application, indicating its seamless facilitation of loan transactions. The integration of additional technologies like Decision Support and SMS notifications enhances risk management and financial transparency, fostering increased capital generation for cooperatives, thereby providing opportunities for business growth and sustainability. The developed Loan Management System offers a streamlined approach compared to traditional methods, facilitating faster loan application, approval, and payment processes. Overall, this research contributes to the advancement of loan management practices in transportation cooperatives by leveraging technology, enhancing decision-making processes, and promoting financial efficiency and transparency.

Biochar also known as ‘biocarbon’ or ‘biocoal’ is a material that has a charcoal similar property. It is obtained from thermolysis (pyrolysis) of biomass feedstocks and plant matters. It can help the process of eliminating carbon dioxide from the atmosphere. The biochar was considered as waste by industrial plants and considered no additional cost except for the transportation. Biochar was tested for its chemical properties in Department of Science and Technology as a parameter for Simapro. Environmental and health impact were analyzed in this study for concrete with biochar as partial replacement for cement. Different mixtures with zero percent to twenty percent biochar replacement was simulated using life cycle assessment with the help of Simapro. Different sources in Luzon island, Philippines were gathered and found out that sources in southern part of Luzon is the best sources for biochar because of its near location that decreases the effect of transportation. Also, concrete with biochar replacement with or without considereing the effect of transportation yields greater health and environmental impact compared to mixture without biochar replacement.

The integration of Internet of Things (IoT) technology in the agricultural sector using advanced sensor systems has garnered significant interest in the recent year, especially in promoting food security. This study shows an application of this to Spondias purpurea (Philippine Pias Prunes), an important fruit in the Philippine Archipelago. The developed system places significant importance on the connection of Internet of Things (IoT) devices and the Google Cloud Platform. This integration enables real-time monitoring, data storage, and analysis, therefore providing valuable insights into enhancing the drying process and mitigating spoilage by maintaining moisture levels within the recommended range of 12-14%. The technology provides farmers with the opportunity to extend the shelf life of the prunes, reduce food wastage and increased profitability. While the system focused on Spondias purpurea, the system is highly adaptable and scalable to other fruits and crops. The research employed a DHT11 sensor that is linked to a Raspberry Pi Microcontroller, together with a Google Cloud-Based Platform for the purpose of data storage and processing. Results of the experiments indicate that the temperature measurements remain consistent at varying conditions. Moreover, the humidity levels remain to be high while the prune’s moisture content continue to be steady. To enhance the system's functionality, future endeavours should focus on integrating the system with other agricultural processes. Additionally, it is recommended to broaden the scope of the cost-benefit analysis by considering aspects such as the initial investment, maintenance costs, energy consumption, and potential rewards in terms of product quality, loss reduction, and increased output.

This study introduces a centralized Business Management System (BMS) tailored for small and mediumsized enterprises (SMEs), with an innovative approach due to the integration of a foot traffic detection system through video processing. The system allows businesses to access common business management features such as point of sales, staff scheduling, inventory management, and reports. With the integration of YOLOv7, foot traffic detection for customer count is made possible through LACAD. By automating data collection and providing foot traffic counts, alongside graphical reports, the system empowers SMEs to make better decisions for their businesses. This research highlights the strategic advantage of leveraging foot traffic insights to drive performance and competitiveness in the modern business landscape. As a guide for the study the researchers used Scrum methodology. The study was then evaluated through a quantitative survey using FURPS with 12 IT professionals and 7 beneficiaries as the respondents where the calculated total weighted mean for both the respondent types resulted in 4.60 which means that the users “Strongly Agree” with the system's overall components.

This study focuses on the evaluation of a faculty Performance Modeling System, recognizing the critical role of faculty performance in educational quality and institutional success. Although previous research has often concentrated on the technical development and predictive capabilities of such systems, this paper shifts the focus to user acceptance and system efficacy from the perspective end-users, the faculty. To achieve this, the researchers propose and apply a Modified Technology Acceptance Model (TAM) as the theoretical framework for evaluation. This modified TAM incorporates specific constructs relevant to the academic environment and faculty roles, such as perceived impact on teaching effectiveness and perceived relevance to professional development, alongside traditional TAM constructs like perceived usefulness and perceived ease of use. The evaluation methodology involves assessing faculty perceptions and attitudes towards the system, utilizing both quantitative and qualitative data to understand factors influencing its adoption and continued use. The findings are expected to provide valuable insights into the practical applicability and user acceptance of faculty modeling systems, guiding future design and implementation efforts to ensure these tools effectively support faculty growth and institutional objectives.