Proceeding of International Conference on Science, Health, And Technology
Title : Proceeding of International Conference Health, Science And Technology Initials : Proceeding of ICOHETECH ISSN (Online) : 2962-634X DOI Prefix : 10.47701 Type of Peer-Review : Double-Blind Frequency : half-yearly Editor in Chief : Riska Rosita Publisher : LPPM Universitas Duta Bangsa Surakarta Abstracting & Indexing : Garuda - Google Scholar - Copernicus
From Knowledge to Adherence: Implementing Health Promotion Model in Hypertension Self-Management Education
Hypertension is a major global health problem and a leading risk factor for cardiovascular diseases, stroke, and kidney failure. Despite the availability of effective treatment, patient adherence to hypertension management remains low, particularly in primary health care settings. This study aimed to evaluate the effectiveness of Health Promotion Model (HPM)-based Self-Management Education (SME) in improving adherence and reducing blood pressure among hypertensive patients in Kunduran, Blora, Indonesia. A quasi-experimental design with a control group was conducted involving 60 respondents, divided equally into intervention and control groups. The intervention group received SME sessions integrating education, over four weeks, while the control group received standard care. Data were collected using an adherence questionnaire and digital sphygmomanometer before and after intervention. Results showed a significant improvement in adherence scores in the intervention group (pre-test: 62.3 ± 8.5; post-test: 75.6 ± 7.9; p < 0.001), whereas the control group demonstrated no significant change (p = 0.224). Moreover, the intervention group experienced a greater reduction in both systolic and diastolic blood pressure compared to the control group (p < 0.05). These findings suggest that HPM-based SME is an effective strategy to enhance adherence and blood pressure control in hypertensive patients within primary care settings.
EFFECTIVENESS OF SAND PLAY THERAPY IN REDUCING EMOTIONAL DISORDERS IN CHILDREN
Emotional disorders in children, including anxiety, depression, and behavioral dysregulation, can significantly impact their development and well-being. This study investigates the effectiveness of Sand Play Therapy as a nonverbal, child-centered intervention for reducing emotional disorders. Using a quasi-experimental design, 20 children aged 5–6 years were assigned to either an experimental group receiving Sand Play Therapy or a control group. Emotional symptoms were measured using the Emotional Behavior Problems Questionnaire before and after a four week intervention. Results showed the pre-post test scores between groups were significantly different (F(1,37) = 21.78, p < 0.001), confirming the effectiveness of the intervention. Its mean a statistically significant reduction in emotional disorder scores among children who received therapy, supporting the efficacy of Sand Play Therapy in promoting emotional healing. These findings suggest that Sand Play Therapy is a valuable therapeutic tool, particularly for children who struggle with verbal expression.
THE RELATIONSHIP BETWEEN KNOWLEDGE AND PREVENTIVE BEHAVIOR HIV/AIDS AMONG STUDENTS AT DUTA BANGSA UNIVERSITY SURAKARTA
Background: HIV is an acronym for Human Immunodeficiency Virus, a virus that can potentially cause AIDS. The human immune system is vulnerable to infection because this virus specifically attacks white blood cells (CD4), making the body less effective at fighting disease. AIDS, which stands for Acquired Immune Deficiency Syndrome, is a series of symptoms caused by the HIV virus,which weakens the immune system. As a result, HIV/AIDS is a fatal disease for which there is no cure and has become a serious public health problem throughout the world, including in Indonesia. Objective: The purpose of this study was to determine the relationship between knowledge and HIV/AIDS prevention behavior among students at Duta Bangsa University in Surakarta. Method: This study used a cross-sectional design to analyze the correlation. A total of 96 students were selected as samples using proportional random sampling. After ensuring its validity and reliability, a closed questionnaire was used to collect data. The Chi-Square test was used for data analysis. Results: A statistically significant correlation between the level of knowledge and HIV/AIDS prevention behavior was found in this study (p-value ? 0.05). Prevention behavior was better among students who had more information. Conclusion: There is a significant correlation between understanding and HIV/AIDS prevention behavior among university students. More extensive health education and awareness campaigns are needed to improve students' understanding and reduce the risk of HIV/AIDS transmission on campus.
UI/UX-ORIENTED DESIGN OF ONLINE MALL APPLICATION INTERFACES
The rapid growth of online shopping, particularly in the fashion industry, has highlighted the need for intuitive and user-friendly application interfaces. This study focuses on designing a UI/UX-oriented online mall application for Batik Solo Laweyan, an Indonesian batik product renowned for its unique quality and motifs. Despite the increasing demand for such products, many online shopping applications still struggle to provide an optimal user experience, with issues such as difficult navigation, insufficient product information, and complex payment processes. The research utilizes the Design Thinking approach, which includes the stages of Empathize, Define, Ideate, Prototype, and Test. This method ensures that the design process remains user-centered, with a clear focus on understanding user needs and addressing the challenges they face. Through interviews, surveys, and direct observation, the study identifies key issues such as poor navigation and lack of detailed product information. The design solutions developed focus on creating an intuitive interface, improving product visualization, enhancing the search functionality, and streamlining the payment process. The final prototype is tested for user feedback, allowing for continuous improvement to achieve a seamless and enjoyable online shopping experience for Batik Solo Laweyan products.
DESIGN OF A PROJECT MANAGEMENT SYSTEM AT CV. KHARISMA KARYA NUSANTARA USING THE CRITICAL PATH METHOD (CPM)
Project delays have a substantial impact on overall implementation performance; therefore, effective control and scheduling mechanisms are essential to ensure time efficiency throughout every phase of work. CV. Kharisma Karya Nusantara frequently encounters delays caused by excessive overtime and an unstructured reporting system that cannot be evaluated in real time. This study aims to design a project management system and analyze the scheduling impact using the Critical Path Method (CPM). The CPM analysis identified a critical path consisting of preparatory work, lower structure levels 1 to 3, ground floor work, upper structure levels 1 and 2, first, second, and third floor structural works, walls and partitions of the second floor, first floor finishing, and final work. The total project duration calculated using CPM was 588 days. When recalculated using Microsoft Project, the duration was reduced to 337 days, resulting in a time efficiency of 251 days. These findings demonstrate that implementing a well-structured and integrated project management system can significantly enhance scheduling efficiency, minimize delays, and optimize overall resource utilization.
Intelligent Surveillance for Mask Regulation in Healthcare Using the YOLOv11 Algorithm
The use of face masks in healthcare settings is a crucial measure in preventing the spread of infectious diseases, particularly since the outbreak of the COVID-19 pandemic. However, public compliance with mask-wearing remains a challenge despite the implementation of various regulations. This study aims to design and develop an automatic mask-wearing detection system by leveraging the YOLOv11 algorithm, which is renowned for its superior speed and accuracy in object detection. The methodology involved collecting a dataset of facial images with and without masks, data labeling, model training using YOLOv11, and evaluating the system's performance in real-world conditions. Test results demonstrate that the system can perform real-time mask detection with a mean Average Precision (mAP) of 0.9, establishing it as an effective solution for supporting health protocol monitoring in medical facilities. Consequently, this system not only enhances monitoring efficiency but also has the potential to minimize the risk of infection spread through an intelligent technological approach.
Copyright (c) 2025 Proceeding of International Conference on Science, Health, And Technology
INTEGRATING TELEMEDICINE INTO HEALTH INFORMATION TECHNOLOGY FOR IMPROVING HEALTHCARE QUALITY
The purpose of this study is to examine how the integration of telemedicine into Health Information Technology (HIT) contributes to the improvement of healthcare quality. The research specifically seeks to identify opportunities, benefits, and barriers associated with embedding telemedicine within digital infrastructures such as Electronic Health Records (EHRs), Health Information Exchange (HIE), and mobile health (mHealth) applications. To achieve this objective, a systematic literature review was carried out using the PRISMA 2020 framework. Relevant studies were retrieved from several open-access databases, including PubMed Central, BMJ Open, BMC Digital Health, JMIR, and the WHO Global Health Observatory. The search was limited to publications appearing between 2019 and 2025. Out of 150 records initially identified, 25 studies met the inclusion criteria after screening and full-text assessment. These studies comprised randomized controlled trials, case studies, reviews, and international health policy documents. The findings reveal five key contributions of telemedicine–HIT integration: improved interoperability, enhanced accessibility, increased operational efficiency, greater patient satisfaction, and better clinical outcomes in chronic disease management. Nevertheless, challenges such as uneven digital infrastructure, data protection concerns, and variable levels of digital literacy remain significant. The study concludes that national policies, adoption of global interoperability standards, and investment in digital health infrastructure are essential to ensure sustainable implementation.
Digital Training Recommendations for Enhancing Healthcare Human Resource Competence Using the Simple Additive Weighting Algorithm
The main challenge in digital transformation within the healthcare sector lies in the limited mapping of human resources’ (HR) readiness toward information technology. This study aims to evaluate the digital readiness level of healthcare human resources using a data-driven approach. The Simple Additive Weighting (SAW) method was applied, utilizing six variables whose weights were determined through expert discussions. The results show that respondents’ digital readiness scores range from 0.800 to 0.858. The highest score was achieved by R011 (Doctor, Outpatient Department) with a score of 0.858, indicating excellent digital literacy and effective utilization of information systems. A score of 0.828 was obtained by R032 (Medical Records Administration, ICU), R035 (Midwife, Polyclinic), and R025 (Doctor, Outpatient Department), suggesting relatively even readiness levels. The lowest score, 0.800, belonged to R026 (Laboratory Analyst, Polyclinic), which still falls within the high-readiness category but indicates the need for improvement in health data analysis skills. The overall average score was 0.828, confirming that the majority of healthcare personnel demonstrate good digital readiness. These findings highlight the effectiveness of the SAW method in providing data-driven recommendations for digital capacity development. Moreover, the results can serve as a foundation for designing more targeted and efficient training programs. Overall, this study demonstrates that SAW-based mapping can effectively support strategic decision-making in the digital transformation of healthcare services.
USABILITY EVALUATION OF EARLY DETECTION AND POSTPARTUM COMPLICATION CONSULTATION SOFTWARE BY POSTPARTUM MOTHERS
The postpartum period is a phase following childbirth that is vulnerable to various health complications. This paper aims to describe postpartum mothers’ assessment of the usability of an early detection and health complication consultation software during the postpartum period. Usability evaluation was conducted using the System Usability Scale (SUS) method to efficiently assess user perceptions of the technology system in terms of satisfaction and acceptance. The paper adopts a descriptive quantitative approach, with methods including questionnaire design, data collection, SUS score processing, result interpretation, and formulation of improvement recommendations. The study results show an average SUS score of 79.67, which falls into the A- category, indicating an acceptable level of user acceptance and a rating scale classified as Good. The majority of respondents found the application useful due to its ease in selecting symptoms, speed of assessment results, and direct consultation features, although there were suggestions for further feature development and service quality enhancement
THE ROLE OF THE WEB AS A COMMUNICATION MEDIA IN IMPROVING PUBLIC SERVICES THE GOVERNMENT
This study aims to describe the role of the web as a communication media in improving public services provided by the Government. This research uses a descriptive method as its type and a quantitative approach. The research location is in one of subdistricts to determine the feasibility of using the web in public service. Data collection through questionnaires was an effective technique to measure and gain insight into what the respondents wanted to convey.The study titled “The Role of the Web as a Communication Media in Improving Public Services The Government,” a closed-ended questionnaire technique was chosen to make it easier and more comfortable for respondents to answer, while also simplifying data collection for the researcher. The results of the study show that the community found the web system easy to understand and use. Furthermore, there was an improvement and acceleration in the administrative services for population documentation. The existence of the population web system has enhanced public services in managing civil administration. Based on these aspects, it can be concluded that public services are very good.
THE ROLE OF MOBILE APPLICATIONS IN ENHANCHING POSTPARTUM MOTHER’S KNOWLEDGE ABOUT POSTNATAL CARE: A SCOPING REVIEW
The high rate of postpartum maternal mortality due to health complications is a serious problem that requires innovative solutions. This research aims to explore the role of mobile applications in increasing the knowledge of postpartum mothers and identify the characteristics of effective educational applications. The method used was a Scoping Review with a population of postpartum mothers, using primary research articles in Indonesian and English from 2015-2025 in the Google Scholar and PubMed databases. Results show that apps such as Aponjon, BIDANKU, and Breast Milk Mother significantly improve mothers' knowledge, practices, and self-efficacy through voice messages, texts, and content tailored to the postpartum stage. Characteristics of effective apps include regular communication, personalization of content, focus on maternal and neonatal care, and high interactivity. In conclusion, mobile applications are a potential educational medium to significantly increase the knowledge of postpartum mothers and must be part of the national maternal health strategy to reduce maternal mortality.
THE EVALUATING MACHINE SAFETY AND SUSTAINABILITY BY CIRCULAR DESIGN: A COMPOSITE INDICATOR
Circular design offers significant potential for creating more environmentally friendly and sustainable machines. However, its implementation also presents a number of challenges, particularly related to operational safety and sustainability evaluation. A comprehensive evaluation approach and clear technical standards are needed to ensure that circularly designed machines remain efficient, safe, and suitable for long-term use. This research method uses a literature review to develop indicators. The results of this article identify 16 indicators that can be used to develop sustainable machine designs. These indicators are divided into two main categories: 8 indicators related to environmental aspects, including energy savings, recycling, reuse, toxic and hazardous materials, number of components, product durability, and environmentally friendly components; and 9 indicators related to technical aspects, including assembly and disassembly, product dimensions, product weight, maintenance, safety of use, ease of operation, ease of cleaning, ease of production, and product adaptability. Furthermore, indicator validation is crucial to ensure that the indicators used are relevant, accurate, and reliable in the context of developing sustainable machine designs.
SMART RECOMMENDATION SYSTEM MODELING FOR BATIK USING THE CONTENT BASED RECOMMENDATION METHOD
Batik was an intangible cultural heritage recognized by UNESCO, with unique variations of motifs, colors, and philosophies in each region, both in Indonesia and Malaysia. The development of the fashion industry and e-commerce brought both opportunities and challenges, since users often had difficulties finding batik that matched their preferences, occasions, or symbolic needs. This research aimed to develop a smart recommendation system model for batik using the content-based recommendation method. The dataset consisted of batik data from Indonesia and Malaysia with attributes such as region of origin, dominant color, main motif, category, and usage. The system development method applied was Prototyping, which included the stages of requirement identification, quick design, and prototype construction. The results showed that the system was able to provide relevant recommendations according to user preferences. For example, when the user selected batik preferences with green color, leaf motif, and casual usage, the system recommended Batik Priangan from Indonesia with the highest similarity value of 0.75. These findings proved that the content-based approach successfully connected batik attributes with user needs. This research was expected not only to simplify the search for batik products in the digital era but also to contribute to the preservation of batik culture through the utilization of information technology.
Optimization of MySQL Database in the Development of Solo Batik Mall
This study aims to design and optimize a MySQL database for an online batik mall system to support the digitalization of batik micro, small, and medium enterprises (MSMEs). The research employed three stages: analysis, design, and implementation. The analysis phase identified actors (sellers, buyers, and administrators) and business process needs. The design stage focused on database structures and optimization strategies, including indexing, query optimization, caching, normalization, and denormalization. The implementation involved building the database, applying optimization techniques, and evaluating performance. The optimization of MySQL significantly improved query execution speed, reduced system response time, and enhanced resource efficiency. The system was able to manage transactions, product searches, and reporting more effectively, supporting both operational and strategic needs of the online batik mall. The MySQL-based online batik mall system provides an efficient solution for data management, thereby enhancing the competitiveness of batik MSMEs in the digital era.
Lung Cancer Disease Prediction Model with Multiple Linear Regression
Lung cancer remains one of the leading causes of cancer-related mortality worldwide, particularly in developing countries where smoking prevalence is high. This study aims to develop a predictive model for lung cancer risk using multiple linear regression based on two main factors: genetic predisposition and exposure to passive smoking. The research was conducted using an observational analytic design with secondary data derived from cancer registries, hospital medical records, and national health surveys. Data processing included cleaning, imputation of missing values, and standardization of exposure variables. The results of the regression analysis showed that both genetic risk and passive smoking significantly increased the lung cancer risk score, with coefficients of 0.24 and 0.48, respectively. Interestingly, passive smoking demonstrated a stronger impact compared to genetic predisposition, indicating its role as a more dominant determinant of lung cancer risk. The model explained 20.5% of the variation in risk, while the remaining was influenced by other factors such as air pollution, occupational exposure, and lifestyle. These findings highlight the importance of strengthening public health policies, particularly tobacco control in public spaces, and implementing targeted risk-based screening strategies. This predictive model offers a practical tool for early detection, efficient allocation of health resources, and effective cancer prevention strategies.
Implementation and Optimization of Saliency Mapping Algorithms in Convolutional Neural Networks (CNN) to Enhance Transparency in Pneumonia Diagnosis
This study aims to develop a transparent and reliable artificial intelligence model for pneumonia diagnosis using chest X-ray images by implementing and optimizing Convolutional Neural Networks (CNN) with Saliency Mapping. The research employed a combination of advanced optimization techniques, including aggressive data augmentation, class weight balancing, L2 regularization, dropout, batch normalization, and adaptive learning rate scheduling to address overfitting challenges. A functional prototype was then deployed in a Streamlit-based application to provide an interactive diagnostic tool. The evaluation results demonstrated that the model achieved strong performance, with high training accuracy and competitive testing accuracy, while visualization through Saliency Mapping provided meaningful interpretability by highlighting critical lung regions, particularly the mid-to-lower lung fields and hilar area. This interpretability ensured that the system not only delivered accurate predictions but also supported clinical reasoning by aligning with radiological characteristics of early-stage pneumonia and bronchopneumonia. The integration into a user-friendly application illustrates the potential for practical adoption in healthcare settings, especially in regions with limited access to radiologists. Overall, the study demonstrates that combining CNN-based classification with explainable AI techniques can bridge the gap between advanced machine learning and clinical applicability, offering a strategic pathway to improve pneumonia diagnosis and patient outcomes.
ENHANCING PHOTOVOLTAIC PERFORMANCE USING TITANIUM DIOXIDE BASED NANO-ENHANCED PCM FOR PASSIVE COOLING APPLICATIONS
The performance of photovoltaic (PV) modules is significantly affected by the increase in operating temperature, which leads to reduced power output and overall efficiency. Therefore, passive cooling strategies are required to maintain stable energy conversion in solar systems. One widely investigated approach is the use of phase change materials (PCM) due to their ability to absorb and release latent heat, although their low thermal conductivity remains a major limitation. This study aims to evaluate the effectiveness of incorporating titanium dioxide nanoparticles into PCM, known as nano-enhanced PCM (NePCM), in improving the cooling performance of PV modules. The experimental method was conducted on a 50 Wp polycrystalline PV module under three conditions: without cooling, with pure PCM, and with titanium dioxide-based NePCM. The preparation of NePCM was carried out using a two-step method involving mechanical stirring and ultrasonic sonication to achieve a homogeneous nanoparticle dispersion. The results demonstrated that the addition of titanium dioxide improved the thermal conductivity of PCM, leading to lower operating temperatures, more stable voltage and power output, and higher energy conversion efficiency compared to both pure PCM and the uncontrolled condition. These findings highlight the potential of titanium dioxide-based NePCM as an effective, economical, and sustainable material for passive cooling applications in photovoltaic systems.
Development of an Image-Based Calorie Detection Model in Indonesian Food for Stunting Prevention
Stunting is a global health problem, especially in developing countries including Indonesia. One of the main causes of stunting is malnutrition, especially in children aged 0-23 months. Therefore, this study aims to develop an AI-based model to detect calories in Indonesian food images for stunting prevention, using the Transfer Learning method with AlexNet. In this article, we propose a new deep learning-based food image calorie detection model called, Alexnet Interactive Transfer Learning (AITL). AITL is built based on Alexnet's Convolution Neural Network architecture, and further modified at the last Convolution layer and classification layer. AITL was evaluated using a dataset from the Indonesian food database. Experiments were conducted on the dataset to detect food types and their calorific content. There are ten classes of authentic Indonesian food types, which include: Rendang, Bika Ambon, Pempek, Sate Ayam, Gado-gado, Ayam Pop, Kerak Telor, Rawon, Lemang, and Ayam Betutu. The accuracy of the developed AITL model reached 95.33%. The results of the tests conducted show that Alexnet-based AITL outperforms other CNNs in terms of accuracy and efficiency.
Design and Development of SmartKuliner: A Multimedia-Enhanced Web Platform for Culinary Product Promotion
This paper presents the design and development of SmartKuliner, a web-based culinary marketplace enhanced with multimedia features to support culinary product promotion. The platform integrates visual design, user-centered interface, and multimedia content to improve user engagement and trust. The development process adopts a multimedia development life cycle (MDLC) and emphasizes usability testing. Results indicate that SmartKuliner provides an effective medium for culinary businesses to promote products and for users to discover trusted local culinary items.
COMPUTATIONAL MATHEMATICAL MODELING FOR LUNG CANCER DISEASE PREDICTION USING MULTIPLE LINEAR REGRESSION
Lung cancer remains one of the most prevalent and deadly types of cancer worldwide, especially in developing countries with high smoking rates and limited early detection resources. This study aims to develop a computational mathematical model for predicting lung cancer risk using multiple linear regression. The model focuses on two primary factors: genetic predisposition and exposure to passive smoking, which are among the most significant determinants of lung cancer. An observational analytic design was employed using secondary data obtained from cancer registries, hospital records, and national health survey datasets. Computational data preprocessing techniques, including data cleaning, missing value imputation, and variable normalization, were applied to ensure model accuracy and reliability. The regression analysis revealed that both genetic predisposition and passive smoking significantly increased the lung cancer risk score, with regression coefficients of 0.24 and 0.48, respectively. The findings indicate that passive smoking has a greater impact on lung cancer risk compared to genetic factors. The final model demonstrated a coefficient of determination (R²) 0.72 indicates that 72% of the variation in risk can be explained by the combination of these two variables. This finding suggests that environmental factors have a more dominant influence than lifestyle factors on increasing lung cancer risk. This computational model provides a practical tool for early detection and risk stratification, supporting public health policies aimed at tobacco control and targeted screening programs to reduce lung cancer incidence and mortality
APPLICATION OF SMART FARMING IN THE USE OF FRESHWATER FISH CULTIVATION WASTEWATER FOR IOT-BASED SANSEVIERIA PLANT IRRIGATION
Modern technology has brought significant changes to various sectors, including agriculture and environmental management. Challenges faced in plant cultivation include limited clean water sources and waste generated from various agricultural and aquaculture systems. The ornamental plant Sansevieria is one type of plant widely used in interior design due to its ability to improve air quality and its attractive aesthetics. By utilizing wastewater from fish ponds as an irrigation medium, it is hoped that these plants will not only be able to grow well and obtain adequate nutritional intake, but can also provide additional benefits in the form of reusing resources previously considered waste. The technology to be developed is based on the integration of the Internet of Things, which utilizes wastewater from freshwater fish aquaculture as an irrigation medium for ornamental Sansevieria plants. The method used is the Research and Development (R&D) method, a systematic approach that aims to develop, test, and refine a product through a series of gradual steps. One of the results of this research is a system that is able to demonstrate its potential in reducing dependence on clean water and providing new uses for aquaculture waste to maintain plant health efficiently.
ANDROID-BASED GUARD MONITORING AND SITE SURVEILLANCE SYSTEM
The System is designed to enhance security operations and ensure accountability among security personnel by integrating mobile technology with real-time data collection, the system improves the efficiency, transparency, and reliability of monitoring activities across designated locations. Developed using the Agile Development Model, the system incorporates key features such as monitoring via QR codes and a timestamp camera that enables guards to take and submit pictures. The software also makes it easier for guards to report incidents, enabling them to document any anomalies they come across while on patrol. Evaluation of the system was conducted using the ISO 25010 Software Quality Framework, with fourteen (14) evaluators including administrators, advisory committee members, and IT experts. The results indicated strong performance: the QR code generation feature scored 4.7, while the user module for real-time incident capture and visited site reporting earned 4.8. Overall, the system achieved a 4.5 rating for functional suitability, 4.3 for both performance efficiency and compatibility, and 4.2 for usability and reliability. Aligned with Sustainable Development Goal (SDG) 9: Industry, Innovation, and Infrastructure, the system promotes innovation in security management and strengthens institutional infrastructure. Upon implementation at the Davao del Sur State College General Services Office (GSO), it is expected to significantly improve patrol compliance, incident documentation, and overall operational performance.
THE POTENTIAL OF CNT-PVA MEMBRANE AS A GREEN TECHNOLOGY ALTERNATIVE
The development of advanced membrane technologies is essential for addressing environmental challenges, particularly in wastewater treatment and oil-water separation. Polyvinyl alcohol (PVA) is a hydrophilic, environmentally friendly polymer commonly used for membrane fabrication; however, it suffers from high swelling and low mechanical strength, which limits its long-term performance. To overcome these drawbacks, carbon nanotubes (CNTs) were incorporated into the PVA matrix to form PVA-CNT composite membranes. CNTs serve as structural reinforcements, enhancing mechanical strength, thermal stability, and inter-chain bonding within the PVA network. The interconnected pore structure and high conductivity of CNTs also improve membrane selectivity and reduce swelling by stabilizing the polymer structure when exposed to water or aqueous solutions. Additionally, the modified surface properties provided by CNTs result in superior fouling resistance, minimizing pore blockage and maintaining water flux over extended operation periods. This study demonstrates that PVA-CNT composite membranes offer a sustainable and energy-efficient solution for separation processes, making them highly suitable for oil-water separation, industrial wastewater treatment, and other filtration applications such as water purification and organic compound removal. The findings highlight the potential of PVA-CNT membranes as a green technology that combines high performance with environmental sustainability. PVA-CNT membranes offer a promising approach for developing next-generation membranes with optimized structural and functional properties for environmental applications.
THE FUNCTIONS OF EXPRESSIVE SPEECH ACTS AND THEIR EMOTIONAL DEPICTION IN THE FILM OF DISNEY’S MALEFICENT
This investigation aspires to identify the functions of expressive speech acts performed by the characters in the film of Disney’s Maleficent. Using pragmatic approach the investigation analyzed how these expressive utterance relate to basic emotions. The qualitative descriptive method was used in the recent investigation; dialogues from the film script were collected, grouped into twelve categories of expressive acts, and examined based on six core emotions. The results indicated that eleven functions of expressive speech acts were identified, they were complaint, lamentation, greeting, compliment, apologies, protest, deplore, boast, praise, thanking, and congratulating. The expressive functions were used to highlight the themes of betrayal and conflict in the film. In addition, the expressive functions reflected the basic emotional states of the characters in the film. The basic emotions emerged in the utterances of expressive functions were anger, happiness, sadness, disgusting, fear, and surprise. These findings suggested that expressive actions not only facilitated communication but also reflected emotional states and narrative conflicts. This research enhances the understanding of how films utilize language to depict complex emotions and enrich character development.
THE EFFECT OF ONE EGG A DAY PROGRAM ON WEIGHT WITH STUNTING IN JETIS VILLAGE
Background: The nutritional status of toddlers is an important indicator of public health. Malnutrition during infancy can impact growth, cognitive development, and the risk of chronic disease in the future. Eggs are a source of high-quality animal protein and have the potential to be a simple intervention to improve the nutritional status of toddlers. Objective: To determine the effect of the 1-egg-a-day program for 1 month on the weight of stunted toddlers. Methods: A quasi-experimental study with a pre-test, post-test, and control group design was conducted on 18 toddlers aged 6–59 months in Jetis Village. The intervention group was given 1 boiled egg daily for 30 days, while the control group received no intervention. Weight was measured using a calibrated scale. Data analysis used a paired t-test due to the normally distributed data. Results: The average weight gain of toddlers was 0.3 kg with a p-value of 0.0001. The highest increase was 0.8 kg. Conclusion: The 1-egg-a-day program for 1 month had a significant effect on weight gain of toddlers in Jetis Village.
DESIGN MAINTENANCE OF STITCHING MACHINE MAINTENANCE BASED ON THE RELIABILITY CENTERED MAINTENANCE (RCM) METHOD
Machine maintenance and repair are essential to maintain optimal machine performance. Downtime is a situation where damage occurs to a machine component or when the machine restarts after undergoing a repair or replacement process. CV Madyotomo is a printing company that experienced a total of 20,114 minutes of machine downtime, resulting in a financial loss of Rp 50,285,550. This study aims to design a maintenance system on the Müller Martini 321 stitching machine at CV Madyotomo using the Reliability Centered Maintenance (RCM) approach. The results of the Failure Mode and Effect Analysis (FMEA) analysis show four critical components, namely bearing (RPN 240), v-belt (RPN 189), shaft gear (RPN 175), and support gear (RPN 160). The critical components are bearing, v-belt, shaft gear, and support gear. The application of the RCM method and the integration of the 5R concept has been proven to minimize downtime, extend the life of critical components, and increase the efficiency of the production process
COPRAS METHOD FOR SELECTING OPTIMAL PUBLIC TRANSPORTATION IN SURAKARTA TO SUPPORT SUSTAINABLE URBAN MOBILITY
This study aims to identify the most suitable public transportation mode in Surakarta to support sustainable urban mobility by applying the Complex Proportional Assessment (COPRAS) method. The research considers six evaluation criteria, namely convenient user, user safety, accessibility and inclusivity, fee, time efficiency, and mobility, which reflect both service quality and efficiency aspects of urban transportation. The alternatives assessed include Batik Solo Trans (BST), van, pedicab, taxi and taxibike (online and manual), representing the main public transport modes available in the city. The methodology involves normalizing the decision matrix, applying the assigned weights to the criteria, and calculating the positive and negative significance values for each alternative, followed by determining their relative significance and utility values. The findings indicate that among the alternatives, van with 100,00 achieved the highest utility value, making it the most appropriate choice for enhancing public transportation services in Surakarta. The results demonstrate that the COPRAS methos provides a systematic and balanced approach for integrating benefit and cost criteria, offering practical insights for policymakers in developing to promote efficient, inclusive, and sustainable urban transportation systems
COMPARATIVE EVALUATION OF HOMOGENEOUS AND HETEROGENOUS CATALYSTS IN THE ESTERIFICATION OF WASTE COOKING OIL
Waste cooking oil is a potential raw material for biodiesel production, yet its reuse poses health and environmental risks due to the presence of carcinogenic compounds and high peroxide values. This study aimed to convert waste cooking oil into biodiesel through the transesterification process using different catalysts—acid (HCl), base (NaOH), and heterogeneous (MgO)—combined with pretreatment methods (untreated, bleaching earth, and banana peel adsorption). The reactions were carried out using ethanol as alcohol, followed by homogenization, heating at 60°C for 1 hour, and settling for 24 hours. The results showed that HCl produced the highest biodiesel yield (up to 3.1792 with bleaching earth treatment), followed by MgO and NaOH. Glycerol was obtained as the main by-product, with the highest values also associated with HCl catalysis. Residues were only formed in reactions involving NaOH and MgO due to their heterogeneous and insoluble nature, whereas no residue was found in HCl-based reactions. Pretreatment with bleaching earth significantly improved biodiesel yield compared to banana peel or untreated samples. In conclusion, acid-catalyzed transesterification of pretreated waste cooking oil, particularly with bleaching earth treatment, provides the most effective route for biodiesel production while also generating glycerol as a valuable by-product.
THEMATIC FIELD SCHOOL OF SHALLOT COMMODITY AS AN AGRICULTUREAL EXTENSION METHODE TO IMPROVE FARMERS, KNOWLEDGE, ATTITUDES, SKILLS AND PRODUCTIVITY
Extension agriculture have important role? for development source Power man agriculture in development agriculture that aims For increase knowledge , attitude , skills And product activity results . Various method extension Already implemented in activity the including school roomy thematic based? approach participatory . Study This aim For know school roomy thematic commodities shallot as method counseling agriculture For increase knowledge , attitude , skills And productivity result . Method study is qualitative descriptive . Informant on study This a total of 30 farmers participant school field . Results study show that school roomy thematic commodities shallot cause a number of matter namely , farmers shallot show category very agree that school roomy increase knowledge And previous skills? they Not yet understand or know . In improvement attitude And productivity results , showing category agree . Recommendation results study is implementation extension agriculture based on participatory with method school roomy thematic more developed again with adapt need farmer .
The Role of Local Wisdom in Driving Innovation and Green Economic Growth through Digital Platforms
This study investigates the transformative potential of integrating local wisdom encompassing indigenous knowledge, cultural values, and traditional ecological practices into digital platforms to drive innovation and foster green economic growth, aligning with global sustainability agendas. It highlights how local wisdom, often manifested in heritage crafts, regenerative agriculture, and community-based resource management, serves as a foundation for eco-friendly production systems, ethical trade, and inclusive entrepreneurship when amplified through digital technologies such as e-commerce, traceability systems, and financial technology. Employing a mixed-method approach involving case studies from Asia, Africa, and Latin America alongside quantitative analyses of export growth, job creation, and supply chain resilience, the research reveals that embedding cultural identity and sustainable practices into digital commerce enhances product authenticity, attracts premium markets, reduces carbon footprints through localized production, and empowers marginalized groups, including women and indigenous communities. The findings underscore that such integration not only contributes to fair trade and decent work but also strengthens biodiversity conservation, promotes circular economy principles, and mitigates socio-economic inequalities. The study recommends implementing policy incentives, digital literacy programs, and multi-stakeholder collaborations between governments, platform developers, and cultural institutions to scale these initiatives, ultimately positioning local wisdom as a strategic driver for environmentally responsible, socially inclusive, and innovation-driven economic transformation in the digital era.