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This study highlights Bajawa Coffee Shop in Bekasi as the main subject in examining the factors that influence customer loyalty. This study aims to analyze the effect of service quality and price perception on customer loyalty, with customer satisfaction as a mediating variable. Service quality refers to the extent to which the service provided is able to meet customer expectations, while price perception is the customer's assessment of the economic value of the product or service received, which is influenced by costs, market demand, and business strategy. Customer satisfaction is a subjective evaluation of the experience of using a service, which reflects how well customer expectations are met by actual performance. This satisfaction plays an important role in building long-term relationships between customers and companies, and has a major impact on loyalty, brand reputation, and business sustainability. Customer loyalty itself is defined as a commitment to continue choosing and recommending a particular product or service, despite offers from competitors. In the context of increasingly tight competition in the cafe industry and the increasing trend of coffee consumption, understanding the factors that shape loyalty is very important. This study uses service quality and price perception as independent variables, customer satisfaction as a mediating variable, and customer loyalty as a dependent variable. The results of this study are expected to contribute to the development of more effective business strategies in retaining customers at the Bajawa Bekasi Coffee Shop.

Green grass jelly (Cyclea barbata) leaves are one of the herbal plants found in Indonesia and have various potential health benefits. This plant is known to contain bioactive compounds such as flavonoids, tannins, and alkaloids that act as antioxidants, anti-inflammatories, and help regulate blood sugar levels in the body. The utilization of green grass jelly leaves is not only as a refreshing traditional drink ingredient, but also as a source of natural medicine that is environmentally friendly and easily accessible to the community.This activity aims to increase awareness and knowledge of students and teachers about the benefits of green grass jelly leaves, as well as teach simple but effective processing techniques to produce value-added processed products.The research method used descriptive qualitative method.The results of this activity showed an increase in participants' understanding and skills in processing green grass jelly leaves into products that are suitable for consumption, as well as fostering interest in utilizing herbal plants as part of a healthy lifestyle.

The phenomenon of online loans has emerged as a financial innovation that transforms the pattern of access to funds within urban communities. The convenience of obtaining loans without complex requirements has contributed to the rise of a consumerist lifestyle, especially among the younger generation. This study aims to analyze the correlation between the use of online loans and the dynamics of consumerist lifestyles in urban society. By employing a literature review and descriptive-qualitative analysis methods, the research reveals that low financial literacy, social pressure, and the influence of social media intensify the tendency toward instant loan-based consumerist behavior. Psychological factors such as FOMO (Fear of Missing Out) and the philosophy of YOLO (You Only Live Once) further reinforce this consumerist behavioral pattern. The results of the study show that the phenomenon of online loans not only impacts financial issues but also causes psychological stress and shapes compulsive consumption patterns.  

Anemia is a hematological disorder that is often not recognized in the adult age group. One lifestyle factor that can affect hemoglobin and hematocrit levels is the consumption of tea or coffee with meals, because the tannin and polyphenol content inhibits the absorption of non-heme iron. Early detection of hemoglobin and hematocrit levels accompanied by education about eating and drinking habits is an important strategy in preventing anemia. This screening activity is carried out using the Plan-Do-Check-Act (PDCA) approach. Examination of hemoglobin and hematocrit levels is carried out using Point-of-Care Testing (POCT) from capillary blood. Education is provided to all participants through leaflets and group counseling regarding the effect of tea and coffee consumption on iron absorption. A total of 91 participants took part in this activity, consisting of 39.6% men and 60.4% women, with an average age of 47.4 years. The average hemoglobin was recorded at 11.2 ± 1.6 g/dL and hematocrit at 33.0 ± 4.7%. As many as 42.9% of participants experienced anemia based on hemoglobin levels below normal values ​​according to gender. Hemoglobin and hematocrit examinations successfully identified a significant proportion of individuals at risk of anemia. Education on the right time to consume tea or coffee and increasing consumption of foods rich in iron and vitamin C are preventive interventions that can be applied to maintain optimal hematological status.   Keywords: Hemoglobin, Hematocrit, Anemia, Iron, Tea, Coffee, Diet

In community service, elementary school children are invited to understand the process of the rice grain chain and how the rice reaches the dining table. This activity not only teaches elementary school children about the rice supply chain, but is also expected to foster a sense of gratitude and appreciation for the food they eat every day. This activity is carried out using interactive storytelling methods using props, discussions and using interactive games. Evaluation is also carried out informally through observations during discussions and games, and by giving short questions to children about their stages and their respective roles. This learning activity contains values ​​from the SDGs, namely ending hunger (SDGs 2) and sustainable consumption (SDGs 12). The purpose of this service is for elementary school children to know the journey of rice from the rice fields to the dining table by using pictures and telling stories for each group, in addition to elementary school children to work together and need each other..    

Anemia in pregnant women is a public health problem that remains high in Indonesia and impacts maternal health and fetal development. This study aims to determine the prevalence of anemia and risk factors in pregnant women at the Saritani Community Health Center, Boalemo. The study used a cross-sectional design on 28 pregnant women selected by purposive sampling. Data were collected through interviews using a structured questionnaire and hemoglobin level examination (HemoCue). Descriptive and bivariate analyses using the Chi-Square test were performed, with p < 0.05 as the significance limit. The results showed a prevalence of anemia of 42.9 % . Factors significantly associated with anemia included education level (p = 0.041), adherence to Fe tablet consumption (p = 0.022), parity (p = 0.037), and pregnancy spacing (p = 0.049). Mothers with low education, non-adherence to Fe tablet consumption, high parity, or pregnancy spacing <2 years had a higher risk of developing anemia. Age and diet did not show a significant association.

College students are in early adulthood, a critical developmental stage marked by physical, psychosocial, and cognitive changes that can significantly impact dietary behaviors, including fruit and vegetable consumption. Adequate intake of fruits and vegetables is essential for maintaining overall health and reducing the risk of non-communicable diseases (NCDs). However, evidence indicates that fruit and vegetable intake among college students often falls below the levels recommended by the World Health Organization (WHO). This study aimed to validate a Semi-Quantitative Food Frequency Questionnaire (SQ-FFQ) for assessing total fruit and vegetable intake among college students in Surabaya City, Indonesia. A cross-sectional study was conducted involving 30 active university students. The SQ-FFQ method produced higher intake estimates compared to the Estimated Food Record. A statistically significant and strong correlation was found between the two methods (p < 0.001, r > 0.7), indicating strong agreement. These findings support the SQ-FFQ as a valid tool for measuring total fruit and vegetable intake in this population.

Post-harvest handling of fish requires an effective cold chain system, including the availability of ice factories, to preserve the quality and freshness of catches. The presence of an ice factory enables fishermen to bring ice during fishing trips, ensuring the catch remains safe for consumption. The planning of a portable mini ice factory in Ciwaru Village, located within the Ciletuh National Geopark, aims to maintain fish quality along the southern coast of West Java. Although several ice factories exist in Sukabumi Regency, their availability at fish landing sites such as the Ciwaru Fish Auction Place (TPI) remains insufficient. According to the Regulation of the Minister of Marine Affairs and Fisheries No. 2 of 2021, assistance for ice factory construction is provided to fishermen groups following a feasibility study submission. This community service project aims to assist fishermen cooperatives in improving cold chain management and preparing a feasibility study for ice factory development. Key issues identified include limited human resource competence, hygiene and sanitation challenges, feasibility study preparation, and internal communication enhancement within cooperatives. Solutions are implemented through training programs, cold chain method applications, feasibility analysis for mini ice factories, and the development of an information system for fishermen. The planned ice factory unit has a capacity of 1 ton per 8-hour cycle, supported by three freshwater wells near the site. Economic analysis reveals an NPV of Rp1,170,676,141, an IRR of 10.91%, and a Net B/C Ratio of 1.64, with a BEP at 311 tons/year, well below the installed capacity of 788 tons/year, confirming its economic viability. The resulting feasibility study will serve as the basis for applying for government assistance, complemented by scientific publications, national media coverage, video documentation, and intellectual property registration.

Based on WHO data, cases of dyspepsia in the world reach 13-40% of the total population each year. Dyspepsia is one type of non-communicable disease that occurs not only in Indonesia, but also in the world. Irregular eating patterns, consumption of certain types of food such as sour, spicy and irritating foods are some of the factors that cause dyspepsia. To determine the relationship between dietary patterns and dyspepsia in female adolescents at the Hidayatullah Tanjung Morawa Islamic Boarding School in 2023. This study uses an analytical observational method with a cross-sectional approach, data collection using questionnaires and interviews. Data analysis using univariate tests and bivariate tests using the chi-square test. The majority of respondents were aged <16 years (70.3%). The incidence of dyspepsia was 70.3% or 45 respondents, of which 25 people (39.1%) had poor diet. Of the 29.7% of respondents who did not experience dyspepsia, 13 people (20.3%) had good diet. The majority of respondents often consumed spicy foods (67.1%) but rarely consumed sour foods (56.2%) and irritative foods (65.6%). The bivariate results between the relationship between diet and dyspepsia, spicy foods and dyspepsia, sour foods and dyspepsia, and irritative foods and dyspepsia were p-values ​​of 0.037, 0.041, 0.013, 0.526, respectively. There is a relationship between dietary patterns, types of sour and spicy foods with the incidence of dyspepsia, but there is no statistically significant relationship between the types of irritating foods and the incidence of dyspepsia in female adolescents at the Hidayatullah Tanjung Morawa Islamic Boarding School.

The prevalence of Chronic Energy Deficiency (CED) in the Riau Islands is a concerning public health issue, with 18.7% of non-pregnant women reported to be affected. In Batam City specifically, 95 cases of undernutrition were recorded in 2024. This study aimed to analyze the relationship between food intake and the nutritional status of women of reproductive age experiencing CED. A descriptive correlational research design with a cross-sectional approach was employed. The study used total sampling, involving 31 women from the Batu Aji KUA in Batam. Data on food intake were collected and compared to recommended dietary standards. The findings indicated that a majority of women had food intake levels below the recommended daily allowance. Despite this, not all of the participants were found to be suffering from CED. Statistical analysis using the Chi-square test revealed a significant association between food intake and nutritional status (p = 0.025, where α = 0.05), suggesting that food intake plays an influential role in determining nutritional outcomes. Furthermore, women whose food intake was lower than the recommended levels were found to have a 0.611 times greater risk of experiencing chronic energy deficiency. These findings emphasize the crucial role of adequate energy and nutrient intake, especially among women of reproductive age, in preventing CED and improving overall health. Improving food consumption patterns in this demographic is essential not only for individual well-being but also as a preventive measure to reduce the risk of stunting in future generations. The study underscores the need for targeted educational interventions to increase awareness about proper nutrition and energy intake among women, particularly those in reproductive age, as a strategy to address undernutrition and its broader public health consequences.

Introduction: The integration of Digital Twin (DT) technology and the Internet of Things (IoT) into Building Energy Management Systems (BEMS) offers a transformative approach to optimizing energy consumption in buildings. This study explores the development of a Digital Twin based BEMS prototype, which leverages real time data collection, predictive analytics, and machine learning to enhance energy efficiency, reduce costs, and support sustainability goals in modern buildings. The research also addresses key gaps in current energy management systems, including real time adaptive control and integration with smart grid platforms. Literature Review: Previous research highlights the limitations of traditional BEMS, which often rely on static control strategies and lack real time adaptability. Recent advancements, including predictive maintenance and machine learning integration, have improved energy optimization. However, challenges such as data interoperability, scalability, and cybersecurity remain. This review consolidates current approaches and identifies opportunities for enhancing BEMS through the integration of DT technology, IoT, and machine learning. Materials and Method: The methodology employed involves the design of a Digital Twin based BEMS prototype, incorporating IoT sensors for real time data collection on variables such as HVAC load, occupancy, and environmental factors. The system uses time series forecasting and adaptive control strategies to optimize energy consumption. A case study building is used for validation, with performance metrics such as energy savings, CO₂ footprint reduction, and peak load reduction assessed to evaluate the system's effectiveness. Results and Discussion: The results demonstrate a significant reduction in energy consumption (up to 50%) compared to traditional BEMS, along with improved forecasting accuracy and sustainability performance. The prototype achieved a high R² score in predicting energy usage, validated through real world application in the case study building. The economic feasibility analysis showed substantial cost savings and a strong return on investment, making the system a financially viable solution for energy efficient building management.

Introduction: Achieving carbon neutrality in industrial systems is essential for mitigating climate change and promoting sustainability. The increasing demand for energy optimization and carbon emission reduction has driven the development of advanced technologies, particularly hybrid machine learning (ML) models. These models, combining ensemble learning and reinforcement learning (RL), offer significant promise in optimizing industrial processes, reducing energy consumption, and improving environmental performance. This study explores the application of hybrid ML models in achieving carbon neutral goals through dynamic process optimization and energy control in industrial settings. Literature Review: Hybrid ML models integrate different machine learning techniques to handle complex and dynamic environments effectively. Ensemble learning methods, such as boosting, bagging, and stacking, combine multiple algorithms to improve predictive performance and robustness. Reinforcement learning (RL), on the other hand, enables real time decision making and adaptation based on trial and error interactions with the environment. In energy optimization, these models are used to reduce energy intensity and carbon emissions, enhancing overall operational efficiency. Previous studies have demonstrated the effectiveness of ML models in energy management, but challenges such as data quality, model integration, and computational complexity remain. Materials and Method: The study applies hybrid ML models combining ensemble learning and RL to optimize energy consumption and minimize carbon emissions in industrial processes. Data from real time sensors and operational parameters are used to train the models. The ensemble learning component improves the accuracy of energy predictions, while RL ensures dynamic process adjustments in response to fluctuating energy demand. The models were tested in various industrial settings, including manufacturing processes, smart grids, and microgrid systems. Performance metrics such as energy efficiency, carbon emissions reduction, and operational costs were evaluated to assess the effectiveness of the models.  Results and Discussion: The hybrid ML models achieved significant reductions in energy intensity (15-20%) and carbon emissions (18-25%). The real time adaptability of the RL component allowed the models to adjust energy consumption patterns dynamically, improving energy efficiency and reducing waste. The models demonstrated their ability to adapt to varying operational conditions, ensuring optimal energy use. A cost-benefit analysis showed that the hybrid models provided substantial energy savings and reduced operational costs, with a return on investment (ROI) of 30-35% within the first year of deployment. However, challenges such as computational complexity and data quality issues were identified, highlighting the need for further refinement in model development.

This study aims to determine the types of fish caught by the local community of Es Wambi village and how the local community of Es Wambi village utilizes the fish caught. The study was conducted from May to July 2024, in Es Wambi village, Okaba District, Merauke Regency. The sampling technique used in this study was non-probability sampling. Data collection techniques used observation, interview, and questionnaire techniques. The results of the study found that the types of fish caught by the local community consisted of 11 types from sea waters and 4 types from fresh waters. Types of fish from sea waters are; stingray (Dasyatis sp), ribbonfish (Trisiulus savala), kuro fish (Eleutheronema tetradactylum), bulanak fish (Mugil chepalus), gulama fish (Jhonius sp), snapper (Lates calcarifer), glass fish (Kurtus guliferi), bambit fish (Selenotoca sp), thorn fish (Chinetodus sp), julung-julung fish (Strongylura-strongylura) and tongue fish (Cynoglassus lingua). Meanwhile, the fish caught from fresh waters are; tilapia (Oreochromis mossambicus), betik fish (Anabas Testudineus), snakehead fish (Chana striata) and tilapia (Oreochromis niloticus). The utilization of fish caught by local people based on observation results is grouped into 3 parts, namely used as consumption fish, sold fresh and processed into salted fish.  

The integration of solar powered IoT irrigation systems in precision agriculture offers a sustainable solution to address water scarcity and enhance crop productivity. By leveraging real time data from soil sensors, weather APIs, and machine learning algorithms, these systems optimize irrigation schedules and improve water use efficiency. This research explores the potential of integrating renewable energy sources, such as solar power, with edge computing in smart irrigation systems to promote sustainable agricultural practices. The study aims to evaluate the performance of the proposed system in terms of water savings, crop yield, energy efficiency, and adaptability to varying climate conditions. Literature Review: Previous studies highlight the importance of smart irrigation systems in reducing water waste and improving crop yield through real time monitoring and automated decision making. However, existing systems often lack the integration of renewable energy and edge computing, which are critical for ensuring sustainability and operational efficiency in rural agricultural settings. The combination of renewable energy with IoT devices offers a promising solution to reduce energy costs and carbon emissions, while edge computing enhances real time data processing, ensuring prompt and accurate irrigation adjustments. Materials and Method: The proposed system integrates solar powered IoT devices, soil moisture sensors, weather data APIs, and edge computing devices to manage irrigation. Machine learning algorithms and evapotranspiration models are used to predict irrigation needs and optimize scheduling based on real time data. The system's performance is evaluated through metrics such as water savings percentage, crop yield improvements, and energy consumption, with a comparative analysis against traditional irrigation methods. Results and Discussion: The results indicate that the system successfully reduces water usage by 30% to 40%, increases crop yield by 25%, and operates with energy autonomy, powered entirely by solar energy. The system's adaptability to varying climate conditions ensures optimal crop growth, even under environmental stresses. The integration of renewable energy and edge computing significantly enhances the sustainability and efficiency of irrigation systems.

The majority of students tend to have irregular eating patterns and often consume unhealthy foods, resulting in nutritional problems such as malnutrition or overnutrition. Malnutrition makes the body more susceptible to infectious diseases, while overnutrition makes the body more susceptible to degenerative diseases. Nutritional status is basically determined by the amount of food consumed and how that food is processed in the body. This study aims to investigate the relationship between macronutrient intake and the nutritional status of female students in the Nutrition Study Program at Unesa. This study is a quantitative study with a cross-sectional design. The respondents in this study were female students in the Nutrition Study Program at Unesa, namely the 2021, 2022, and 2023 cohorts, totaling 247 students. Nutritional status data were obtained from weight and height measurements, while macronutrient intake data were obtained from food consumption measurements using a 3x24-hour food record form. Data analysis in this study used the chi-square test. The results of the chi-square test showed that there was no relationship between carbohydrate intake, fat intake, and protein intake with the nutritional status of female students in the Nutrition Study Program at Unesa.

Aquaculture is a vital sector in global food production, providing essential protein sources. However, the industry faces significant challenges, including high energy consumption and environmental impact. The integration of renewable energy, particularly solar power, with automation and IoT systems offers a promising solution to enhance energy efficiency, sustainability, and productivity in aquaculture operations. This study aims to evaluate the effectiveness of solar powered autonomous systems in reducing energy usage, improving operational efficiency, and promoting environmental sustainability in aquaculture. Literature Review: Recent research has explored various technologies, such as Digital Twins (DTs) and Precision Fish Farming (PFF), which integrate IoT sensors for real time monitoring and optimization of fish farming operations. The combination of Artificial Intelligence (AI) and the Internet of Things (IoT), known as AIoT, has further advanced the industry by enabling automated decision making and predictive analytics. Solar power integration with IoT systems has been shown to significantly reduce operational costs, minimize carbon emissions, and enhance the sustainability of aquaculture practices. These advancements have the potential to address the challenges of energy consumption and environmental degradation in the industry. Materials and Method: This research utilizes a hybrid solar powered IoT system for aquaculture, integrating solar panels, IoT sensors, and automated control systems. The system monitors key water quality parameters, such as pH, dissolved oxygen, turbidity, and temperature, to maintain optimal conditions for aquatic life. Data is collected through IoT sensors and analyzed through a cloud-based platform. A pilot study is conducted on a small scale aquaculture farm to evaluate the system's performance, including energy consumption, water quality management, and fish health. Energy savings, operational efficiency, and environmental impact are assessed. Results and Discussion: The integration of solar powered IoT systems significantly reduced energy consumption compared to traditional systems, with a notable decrease in grid electricity reliance. The system successfully maintained optimal water quality conditions, enhancing fish health and growth. Solar powered systems proved reliable, even in regions with variable sunlight, and demonstrated improvements in operational efficiency through automation. The environmental benefits were evident, with a reduction in carbon emissions and lower operational costs. The study highlights the feasibility of solar powered IoT systems as a sustainable solution for modern aquaculture operations.

The development of electric propulsion systems has become a major focus in efforts to provide energy-efficient and environmentally friendly air propulsion technology. One emerging innovation is the electric motor-based turbojet fan, which is expected to replace conventional fossil-fueled systems. As the need for energy efficiency increases, studies on electrical power consumption and airflow performance are crucial in supporting the development of new-generation propulsion systems. This study aims to evaluate the relationship between nozzle angle and the characteristics of electrical power consumption and airflow velocity in a double-spool turbojet fan. The method used is an experimental test with an ESP32-based control system. The duty cycle is set at 80% to maintain operational stability. Research data is obtained through measurements of electrical current, voltage, and airflow velocity. The nozzle angle variations tested include 13°, 19°, and 25°. The test results show a significant difference between nozzle angle variations on electrical power consumption and wind speed performance. The 13° nozzle angle produces the highest electrical power consumption, indicating a greater energy requirement to maintain airflow. Conversely, the optimal wind speed was found at an angle of 19°, indicating a balance between energy efficiency and aerodynamic performance. Meanwhile, an angle of 25° showed a decrease in performance in terms of both power and speed, making it less effective. In conclusion, the nozzle configuration has a direct influence on energy consumption and fluid dynamics in electric turbojet fan systems. This research provides an important contribution to the design of electric-based propulsion systems by emphasizing efficiency and performance aspects, while supporting the transition to environmentally friendly technologies.

Eco riding/driving is an approach to driving that aims to optimize fuel efficiency and reduce environmental impact. This technique guides drivers to avoid sudden acceleration and braking in order to maintain a stable speed, maintain optimal tire pressure and carry out regular vehicle maintenance. This technique helps save fuel, reduces greenhouse gas emissions, and extends vehicle life. The aim of this research is to determine the level of understanding of students in the automotive engineering education study program regarding Eco Riding. This research is a survey research carried out from July - December 2024 to 56 students in the automotive engineering education study program at Muhammdiyah University, Purworejo. The research data were analyzed using quantitative descriptive analysis. The research results showed that the level of students' understanding of Eco Riding was in the high category at 50%, followed by the medium category (32.1%), rendang category (14.3%) and very high category at 3.6%.

Fish plays a vital role in early childhood development due to its high nutritional value, yet consumption among preschoolers in Indonesia remains low. This study explores the effectiveness of combining hypnoparenting and storytelling as a complementary nursing strategy to promote fish consumption in young children. A quasi-experimental design with a pretest–posttest control group was used, involving 30 preschoolers divided into experimental and control groups. The experimental group received a four-week intervention integrating hypnoparenting and storytelling, while the control group received standard education. Dietary intake was assessed using a Food Frequency Questionnaire (FFQ). Results showed a significant increase in fish consumption in the experimental group (p = 0.000), with no significant change in the control group (p = 0.102). The Mann-Whitney U test also confirmed a significant difference between the groups (p = 0.000). These findings suggest that integrating hypnoparenting and storytelling is an effective, family-centered complementary nursing approach to promote healthier eating habits. This innovative method offers potential in supporting preschool children’s nutrition and overall development through engaging and parent-involved strategies.

This study is to find out how using Instagram for digital marketing affects the rise in brand recognition among small businesses that make things in Malang City. This study uses a quasi-experimental design with both a control group and an experimental group. It then analyzes the data using the Wilcoxon Signed-Rank Test. The study's results demonstrate that digital marketing methods led to a big rise in all measures of brand awareness, such as recall, recognition, purchase, and consumption. The p-value from the difference test shows that social media marketing works to make people more aware of your brand. This study argues that small and medium-sized businesses (SMEs) should make the most of Instagram to improve their marketing and engagement.