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From AI to Experience How Personalization Shapes Online Shopping Journeys in E-Marketplaces
No full textThe rapid convergence of e-commerce platforms and social media has transformed the way Indonesian consumers experience online shopping. This study, titled “From AI to Experience: How Personalization Shapes Online Shopping Journeys in E-Marketplaces in Indonesia”, aims to analyze the role of artificial intelligence (AI)–driven personalization in influencing consumer behavior, satisfaction, and loyalty in digital marketplaces. Using the recent development of social commerce integration into e-commerce, particularly the merger of TikTok and Tokopedia, as a contextual backdrop, the research highlights how recommendation algorithms, chatbots, and personalized content contribute to consumer decision-making processes. A quantitative method with Structural Equation Modeling (SEM) is employed to examine the relationships between AI service quality, personalization, customer experience, and purchase intention. The findings are expected to demonstrate that personalization not only improves efficiency and engagement in online shopping journeys but also fosters trust and long-term consumer loyalty. This study contributes to the literature on AI-enabled retail in emerging markets, positioning Indonesia as a key case for understanding the future of e-commerce in Southeast Asia
Sustaining Digital Transformation: The Human Touch in AI Adoption for Economic Resilience in Malaysia’s Financial Sector
No full textThis paper examines the critical role of the human touch in fostering sustainable adoption of generative artificial intelligence (GenAI) within Malaysia’s financial sector. Drawing upon insights from recent Bank Negara Malaysia surveys, which reveal that only 20% of C-suite executives actively engage with GenAI tools, the study underscores the leadership gap that constrains inclusive digital transformation. Anchored in the literature on emotional intelligence and trust in technology-driven change, the paper employs a conceptual analysis informed by industry reports, regulatory frameworks, and recent empirical findings. The discussion highlights how leaders equipped with emotional intelligence can reduce resistance to technological change, inspire workforce adaptability, and build trust in AI-driven systems, thereby strengthening both organisational resilience and sectoral sustainability. Furthermore, the study situates AI adoption within broader discourses of sustainable economic development by linking technological innovation to human capital enhancement, ethical governance, and inclusive financial services. Findings suggest that balancing automation with the human touch is indispensable for ensuring that AI-driven transformation supports productivity, equity, and long-term sustainability. The paper concludes with policy recommendations, emphasising leadership development, responsible AI governance, and targeted workforce reskilling as key enablers of sustainable digitalisation in Malaysia’s financial sector
Characterization of Tamarindus indica L. Leaves Herbal Tea as a Functional Beverage
No full textTamarindus indica leaves possess great potential as they are rich in antioxidants and suitable for consumption as a functional beverage. Processing T. indica leaves into herbal tea can enhance their usability and benefits. This study aimed to investigate the effect of drying time and temperature on the quality of T. indica leaves herbal tea and the antioxidant characteristics of its infusion. A Randomized Block Design (RBD) was employed with two factors: drying time (2 and 3 hours) and drying temperature (40°C, 50°C, 60°C), resulting in six treatment combinations, each replicated three times. The parameters analyzed in the tea powder included moisture content, ash content, and color intensity (L, a*, b*), while the infusion was analyzed for antioxidant activity, pH, and organoleptic properties (color, aroma, and taste). The results showed that both drying time and temperature significantly affected the moisture content, ash content, color intensity (L, a*, b*), antioxidant activity, pH, and sensory attributes. The best treatment was drying for 2 hours at 40°C, producing a tea with moisture content of 3.13%, ash content of 5.20%, color intensity L = 57.12, a* = 6.10, b* = 16.68, antioxidant activity of 8.24%, pH of 2.70, and organoleptic scores (neutral) for color (3.36), aroma (3.32), and taste (3.36)
Utilization of Carbide Welding Waste as an Alternative Cement Mixture for Concrete Compressive Strength
No full textThis research was conducted to investigate the utilization of carbide welding waste as a cement mixture on the compressive strength of concrete with a target quality of Fc 25 MPa. The test specimens were cylindrical, with a diameter of 15 cm and a height of 30 cm. Concrete mixtures incorporated carbide welding waste as a partial cement substitute, with variations of 5%, 7%, and 10%, compared to a conventional control mixture based on cement volume. A total of 16 cylindrical specimens were prepared. Compressive strength tests were conducted at 7 and 28 days. The designed concrete strength was Fc 25 MPa. The results showed that the use of carbide welding waste in concrete mixtures led to a decrease in compressive strength at 7 days compared to concrete without waste. However, at 28 days, compressive strength increased significantly, especially at certain percentages. At the optimal percentage, carbide welding waste was proven to improve the compressive strength compared to normal concrete, thus demonstrating its potential as an effective cement mixture
Firebase-Integrated Mobile Platform for Swipe-Driven Job Matching
No full textThe swift transition to mobile-first recruitment platforms necessitates the implementation of systems for job matching that are more intuitive, efficient, and engaging. Current employment portals rely on text-dense listings, redundant forms, and restricted personalization, resulting in low match accuracy and, subsequently, diminished user interest. SwipeRight is a mobile application that combines the swiping interaction model with real-time data synchronization and AI-driven profile analysis to address these discrepancies. The objective is to enhance candidate-employer compatibility by facilitating smoother navigation, improving personalization, and alleviating the strain of manual screening. This solution utilizes Flutter for cross-platform deployment and Firebase for authentication, data storage, and real-time updates. Additional AI-driven elements, including Named Entity Recognition (NER), resume parsing, and TF-IDF with cosine similarity, are incorporated for the automated extraction of talents and experiences, hence facilitating a systematic job-recommendation framework. The application architecture has layers for presentation, business logic, services, and data administration. Experimental assessment and initial user comments indicate expedited application procedures for candidates and diminished shortlisting duration for recruiters. The real-time notifications, dynamic resume generation, and swipe-based filtering markedly improved user experience and engagement. Overall, SwipeRight offers a far more effective and user-centric mobile solution for job matching, establishing a readily scalable foundation for the advancement of AI-driven recommendation
Manual Soft-Tissue Mobilization in the Management of Hypertrophic Burn Scars: A systematic Review
No full textBurn scars continue to be a prominent public health problem worldwide, and even in developed nations, survivors of such injuries often develop hypertrophic scars due to excessive collagen deposition, pain, pruritus, cosmetic issues, and limited mobility. This systematic review aimed to identify the effectiveness of soft tissue mobilization (STM) manual techniques in the treatment of hypertrophic scars in burn patients. An extensive search was performed in the electronic databases of the PubMed, Scopus, Google Scholar, and Cochrane Library for published literature from 2017 to the present using the search terms “burn,” “hypertrophic scar,” “massage,” “soft tissue mobilization,” and “manual therapy” using the Boolean algorithm. A total of 11 studies, following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analyses, fulfilled the inclusion criteria and thus rendered the systematic literature review. The literature included consisted of randomized controlled trials, quasi-experiments, and systematic reviews of burn patients that utilized STM. There was a positive correlation of STM techniques such as circular massage, linear massage, Deep Tissue Massage, and Cross Friction in the STM approach to improved scar elasticity, thickness, pain, itching, and mobility in the included literature in comparison to conservative treatments. This systematic literature review shows that STM is a novel, non-invasive method of adjunct rehabilitation in patients suffering from post-burn scars in medicine
Combined Effect of Incentive Spirometry and Diaphragmatic Exercise on Respiratory Outcomes Post Upper Abdominal Surgery: A Literature Review
No full textBackground: Upper abdominal operations mainly cause respiratory complications because the incision across the abdominal region reflects in decreased diaphragmatic movement
, e.g., atelectasis and pneumonia. Incentive spirometry (IS) and diaphragmatic breathing exercises (DBE) are the most employed interventions to enhance lung function and minimize these complications. Although each of these has been demonstrated with positive results individually, their interactive effects on respiratory recovery after surgery are not fully understood. The present literature review investigates the synergy between IS and DBE in respiratory outcomes after upper abdominal surgery, particularly concerning lung volumes, oxygenation, and minimizing postoperative pulmonary complications.
Objective: This review aims to evaluate the combined effect of incentive spirometry and diaphragmatic exercise on improving respiratory outcomes in individuals recovering from upper abdominal surgery.
Methods: A web-based literature search was conducted using PubMed to identify studies on the combined effects of incentive spirometry and Diaphragmatic exercises. The search focused on their impact on peak expiratory flow rate, breathing patterns, and chest expansion in post-operative upper abdominal surgery patients. Titles and abstracts were screened, and relevant articles were included. Additionally, secondary searching was performed by reviewing reference lists for relevant citations.
Result: The review suggests that incentive spirometry and diaphragmatic exercises impact Respiratory outcomes i.e. PEAK EXPIRATORY FLOW RATE, breathing patterns, and chest expansion. However, the combined approach appears more effective, as mean differences indicate. This highlights the potential benefits of integrating incentive spirometry and diaphragmatic exercises in postoperative care.
Conclusion: The review indicates that incentive spirometry and diaphragmatic exercises enhance respiratory outcomes in individuals recovering from upper abdominal surgery
Automatic Detection of Damaged Roads and Lane Detection using Deep Learning
No full textThis project introduces an automated system for detecting road surface damages and identifying lane markings using Deep Learning, YOLO (You Only Look Once), and Canny edge detection. The main goal is to improve road safety, assist autonomous navigation, and support efficient infrastructure maintenance. Road damages, such as potholes and cracks, are detected in real-time from images or videos captured by cameras mounted on vehicles or drones. The YOLO algorithm is used to classify and localize these damages with high speed and accuracy. At the same time, the Canny edge detection method identifies lane boundaries, ensuring precise lane detection even in challenging environments. Combining these techniques results in a reliable and scalable solution for smart transportation systems. The system reduces the need for manual road inspection and enables authorities to prioritize repairs based on real-time information. It also supports safer navigation for autonomous and assisted vehicles
Solar-Powered Filtration: An Investigation into Clean Water Treatment Performance
No full textUntreated wastewater significantly threatens both environmental health and human well-being, highlighting the importance of effective water treatment worldwide. This study evaluates a solar-powered filtration system as a practical alternative, especially for areas with limited infrastructure. The system uses solar panels to drive a water pump and filtration unit, with Powdered Activated Carbon (PAC) and aluminum sulfate serving as the primary filtration materials. Tests were carried out on samples from rivers and wells. Laboratory analysis showed that, after treatment, river water contained Fe = 0.81 mg/L, Mn = 0.08 mg/L, and hardness = 106.8 mg/L, while well water contained Fe = 0.26 mg/L, Mn = 0.04 mg/L, and hardness = 53.4 mg/L. These results indicate a substantial reduction in contaminants, bringing water quality close to clean water standards. Overall, the solar-powered system presents an effective, renewable, and eco-friendly method for producing safe water in remote or infrastructure-limited regions
Ethics and Sustainability in the Lifestyle and Food and Beverage Sector: Governance, Accountability, and Stakeholder Value in Mud and Hound PCL
No full textThis extended abstract examines the ethical performance and sustainability practices of Mud and Hound Public Company Limited (MUD), a major Thai lifestyle and food and beverage enterprise. The objective is to assess governance, accountability, and stakeholder value creation through a multi-framework analytical approach that includes ethical stakeholder analysis, ethical SWOT analysis, Carroll’s CSR model, the Sustainability Compass, Circles of Sustainability, and cautionary versus pre-actionary principles. Data were obtained from Mud and Hound’s annual reports, ESG disclosures, financial statements, and industry benchmarks. The findings reveal strong performance in governance, ethical responsibility, labor rights, and stakeholder engagement; however, significant gaps remain in ecological sustainability, supplier transparency, biodiversity action, and long-term shareholder value creation. Total shareholder return declined by -57.7% over five years, indicating misalignment between corporate strategy and investor expectations. This study highlights the need for MUD to embed measurable sustainability metrics and proactive environmental commitments to strengthen accountability and stakeholder trus