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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.

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.

Oka Jamur Bali is one of the oyster mushroom cultivation farmers. Lack of efficiency in regulating temperature and humidity in mushroom barns is an important factor in the growth of mushroom fruiting bodies. This condition requires an innovative solution to regulate and monitor temperature and humidity in the barn area. This research aims to build a prototype using Arduino UNO, ESP32, DHT11, pump and Internet of Things (IoT) technology.  The monitoring system design uses Arduino UNO, NodeMCU ESP32, DHT11 and DC pump with 12V voltage. Arduino UNO functions as a control system to manage and control the temperature and humidity parameters of the mushroom barn environment with the DHT11 sensor used to accurately measure temperature and humidity. The combination of NodeMCU ESP32 and Arduino UNO aims for monitoring through the ThingSpeak platform which can be accessed with a smartphone connected to the internet network. Based on the results of the prototype of the automatic temperature and humidity control system, the system is able to measure the environmental conditions of the mushroom barn with humidity measurement results in the range of 79% - 82% and the average temperature during the test reached 29.35°C. The application of the system was able to reduce the temperature by 2.28% with an average temperature of 28.19°C and increase the relative humidity by 6.27% with an average humidity of 81.1% in the mushroom barn area. The results of income between the income generated by using the automatic temperature and humidity control system tool and the income of farmers without using the tool increased by Rp. 16,416.

Snack bar is a food product made from a combination of ingredients that are bound together by a binding agent. One type of snack bar is a protein bar. A potential primary ingredient for making high-protein snack bars is tofu dregs. "The protein content in tofu dregs is relatively high about 26.6% and has not been optimally utilized and often becomes waste and pollutes the environment. The production of snack bars can incorporate various ingredients, one of which is red beans. Red beans are a source of plant-based protein, containing about 11% protein. This research aims to develop a snack bar with the best formulation of red bean paste and tofu dregs flour in terms of sensory and chemical characteristics. The research was conducted using a Randomized Block Design with one factor, that is the formulation with five ratio comparisons of tofu dregs flour to red bean paste: r1 (90:10), r2 (80:20), r3 (70:30), r4 (60:40), and r5 (50:50), each with five repetitions. The results revealed that the snack bar with a tofu dregs flour to red bean paste ratio of 60:40 was the best treatment, with physicochemical characteristics of 19.34% moisture content, 1.98% ash content, and 6.81% protein content as well as sensory characteristics including aroma 3.8 (liked), taste 4.17 (more liked), texture 3.9 (liked), and color 3.73 (liked).

Casavva tape chips made from fermented yellow cassava (tape) and tapioca flour with a focus on the proportion of tape (fermented cassava) and tapioca flour. This study used single anova and duncan test to analyze the differences in sensory characteristics between three different proportions of yellow cassava tape and tapioca. The findings revealed that the combination of 75% fermented yellow cassava(tape) and 25% tapioca flour produced the most preferred shape, characterized by a uniform and attractive appearance, with an average score of 2.80, indicating a round shape with relatively neat edges. In contrast, a higher proportion of tape (85%) produced a softer and less stable dough, which led to a less desirable round shape. In addition, color analysis showed that the same proportion (75% tape and 25% tapioca) also produced the brightest and most attractive color, with an average score of 2.89. These results indicate that adjusting the ratio of tapioca flour can significantly improve the sensory quality of cassava tape chips, making them more attractive to consumers. The study concluded that the inclusion of tapioca flour improved dough stability, resulting in better shaped and colored chips, which could benefit manufacturers aiming to improve product quality.

Socks are essential daily wear that require special care, including an effective drying process to prevent unpleasant odors and the growth of bacteria and fungi. Conventional drying methods often face challenges, especially in high-humidity environments or during unfavorable weather conditions. This study aims to design and develop a prototype sock dryer that is more efficient and hygienic. The prototype utilizes a combination of a heater, UV lamp, and humidity and temperature sensors to ensure optimal drying without damaging fabric fibers. A microcontroller-based control system using Arduino Uno is implemented to regulate device operation and monitor sock conditions during drying. Testing results indicate that the device effectively dries cotton socks in damp conditions faster than conventional methods. Additionally, the sterilization feature with a UV lamp helps reduce the risk of microbial growth. This innovation is expected to provide users with a practical, hygienic, and efficient way to dry socks without depending on weather conditions. Further development can be carried out to enhance drying capacity and energy efficiency.

Introduction: ED (Eating Disorders) is one of the most difficult mental disorders to treat and treat, and the cost is even higher than schizophrenia. Secondary somatic complications due to malnutrition, severe weight loss and low levels of micronutrients. Objective: To determine the effectiveness of a combination of interventions such as Expression Head Massage, Myofacial Release, Neurosenso Komplit, General Massage, Patterning, Play Therapy, Brain Gym, Oral Reflex Stimulation. Method: A single-subject study was conducted on a 22-month-old child with ED. Results: The results of the sensory examination evaluation showed an increase in sensory in the child. Conclusion: A 22-month-old child was diagnosed with Eating Disorder, initially given physiotherapy, the child did not want to eat rice at all, only wanted to drink milk and sometimes the child liked to hit and bite, but after doing routine physiotherapy and home programs, now the child is willing to feed 15 mouthfuls of rice and focus on the child has also begun to exist and the child's balance is increasing.

This research aims to design and develop a motion detection-based automatic light control system with a light intensity setting feature using IoT technology. The system utilizes a combination of PIR sensor, MOSFET module, and Arduino Uno microcontroller to control lighting based on the presence and position of the user. With an adaptive control algorithm, the lamp can dynamically adjust the lighting intensity to several levels as needed. Test results show that the system successfully reduces energy consumption optimally without reducing user comfort. The implementation of this technology has great potential in supporting energy efficiency in public areas, such as parks, office hallways, and sidewalks.

Velva, a kind of frozen dessert, made from fruit that contains nutrients and help the body's metabolic processes as a source of energy. Red dragon fruit (Hylocereus polyrhizus) is used in the production of velva in order to get a good color and Moringa to increase antioxidant activity.  The purpose of this study was to determine the appropriate substitution ratio between velva, dragon fruit, moringa leaf extract, and stabilizer to produce dragon fruit velva with good characteristics, namely high antioxidant and preferred by consumers.  This study used a factorial completely randomized design (CRD).  The factors used were the concentration of Moringa leaves (8, 10, 12 g) and the concentration of the type of stabilizer (CMC 1,26%, cornstarch 1,26%, carrageenan 1,26%).  The best chemical analysis was treatment concentration of carrageenan stabilizer 1,26% with the addition of 8 g Moringa leaf extract with antioxidant activity 16,85%, crude fiber 0.63%, vitamin C 4,33%, reducing sugar 11,83%, total phenolic 13,93mg.GAE/ml and pH 3,5.  Physical analysis with melting power 47.00 minutes/hour, overrun 13,00%, TPT 4˚Brix and TAT 1.14%.  The results of the red dragon fruit velva sensory test with various types of stabilizers and the addition of Moringa leaves, as well as the combination of treatments between the two had no significant effect on color, texture, taste, aroma and overall preference.  The best organoleptic analysis was the P3K1 treatment (concentration of carrageenan stabilizer 1,26% with the addition of 8 g Moringa leaf extract) with a color value of 3.06, taste 2.57, aroma 2.78, texture 3.50 and overall preference 3,42.

Child development problems are also related to learning and education problems. In the learning process, a combination of psychosocioemotional, psychomotor skills, medical, and language relationships is needed. These four things are the main keys or gateways to a bright future, especially for children who have learning problems. This study discusses learning media used to train sensory and motor skills of children with special needs using the socialization and demonstration method at St. Anna Tomohon Special School. The phenomenon found at St. Anna Tomohon Special School is that they have problems with sensory, motoric, and learning processes. This results in disruption of the child's physical development. The purpose of creating a sensory playmat is to train good coordination between the five senses and movement to the stimulation received. Located at St. Anna Tomohon Special School, with 21 participants in the activity. Various reactions were found when children demonstrated which were tested by imitating and following games such as acceptance and rejection

This research aims to develop innovations in the manufacture of cookies with the addition of sorghum flour and mung bean flour (Vigna radiata) as the main ingredients. Sorghum flour was chosen because it has a high fiber content, is gluten-free, and rich in antioxidants. Mung bean flour was chosen because it is rich in vegetable protein, fiber, vitamins, and minerals that are important for health. The main objective of this study was to evaluate the effect of adding both types of flour on the physicochemical characteristics, texture, taste, and color of cookies. The research method involved the formulation of various proportions of sorghum flour and mung bean flour, as well as organoleptic tests to assess consumer preferences. Tests were conducted using chemical analysis to determine nutrient content as well as sensory tests to assess texture, taste, and color attributes. The results showed that the addition of sorghum flour and mung bean flour can increase the nutritional content of cookies, especially in terms of fiber and protein.In addition, the combination of these two flours provides a crispier texture and distinctive flavor, which is different from conventional cookies. Overall, this innovation offers a healthier alternative for consumers without compromising the sensory quality of the cookies. The use of sorghum flour and mung bean flour in making cookies not only increases the nutritional value but also fulfills the market need for healthier food products. These findings make an important contribution to the development of functional food products that can be accepted by various groups of people.

Background:  Air pollution has become a serious issue, prompting considerations on obtaining essential substances known as antioxidants for the body. Preventive measures can be taken by utilizing herbal plants such as binahong and mint, known for their antioxidant properties.Objective: Measure the activity of the radical barrier of DPPH powder drink. Method: This study was a genuine research type. Results: Phytochemical screening revealed the presence of alkaloids, tannins, and saponins in the positive samples. The inhibition activity results for single formulations were as follows: binahong formulation 83,835%, mint formulation 85,011%, formulation (1 : 1) 83,043%, formulation (1 : 2) 83,210%, and formulation (2 : 1) 81,259%. Organoleptic tests indicated that formulation III was acceptable based on sensory evaluation. Conclusion: The powdered drink combination of binahong and mint leaves contains antioxidant compounds: alkaloids, flavonoids, tannins, and saponins. The highest DPPH radical scavenging activity was observed in the single mint leaf formulation and the lowest barrier is in combination powder drinks with (1 : 1) formulation, and formulation (1:1) was most acceptable based on sensory evaluation and there is no influence of variation between powdered drink formulation series..    

In this era where the development of digital technology is increasingly sophisticated, because of the role of the flip-flop which can display its function as the basis of a counter. The counter circuit is a combination of combinational and sequential circuits consisting of basic logic gates, flip-flops and other ICs. This research uses experimental methods to design, build and test the performance of the counter circuit system directly. The main components used include IC, seven segment display and sensors. The design is carried out by creating a truth table to ensure the desired constraints on the circuit being created, circuit schematic and PCB layout. The research results show that the designed counter circuit can count up to 256 and will reset to 000 after reaching that limit.

Snack bar is a stick-shaped snack made from flour, seeds and nuts. This research aims to determine snack bar products made from a mixture of millet flour ad arrowroot flour with the addition of walnuts, including physical properties (L*a*b* color values), chemical properties (water, ash, fat, protein and crude fiber contents), and sensory properties based on hedonic test. This study was experimental using Complete Randomized Design (CRD) with the percentage ratio treatments of millet flour and arrowroot flour consisting of formula S1 ((20%:80%); S2(30%:70%); S3(40%:60%); and S4(50%:50%). The data obtained were processed using the Variance Analysis with a confidence level of 95% (α=0,05), and Duncan’s follow-up test. Snack bars have color values L* 41,660-52,580; color a* 6,6317-9,0667; color b* 19,9017-23,9667. The results of proximate analysis showed that snack bars contains 13,7176-17,8433 of water; 0,8459-1,4455% of ash; 5,8175-7,3264% of protein; 20,5320-24,2649% of fat; 48,7558-50,1120%; and 3,6339-5,1826% of crude fiber. Millet flour increases ash and protein content, but fat and crude fiber content decrease. Based on the hedonic test, it is known that panelists liked the taste and texture of S4 snack bar with an average score 3,94 and 3,68; while for the aroma in the treatment of S3 snack bar with an average score of 3,97 and the color in the treatment of S2 snack bar with an average score of 3,97 (hedonic test scale 1=very dislike, 2=dislike, 3=neutral, 4=like, 5=very like). Snack bars combination 30% millet flour:70% arrowroot flour have the best chemical characteristics (value 1,167) and the best sensory characteristics on snack bars from combination of 50% millet four:50% arrowroot flour (value 0,745) based on the DeGarmo effectiveness index test.

This study proposes an approach for human fall classification utilizing a combination of Weighted Moving Average (WMA) and Convolutional Neural Networks (CNN) on the SisFall dataset. Falls among elderly individuals pose a significant public health concern, necessitating effective automated detection systems for timely intervention and assistance. The SisFall dataset, comprising accelerometer data collected during simulated falls and activities of daily living, serves as the basis for training and evaluating the proposed classification system. The proposed method begins by preprocessing accelerometer data using a WMA technique to enhance signal quality and reduce noise. Subsequently, the preprocessed data are fed into a CNN architecture optimized for feature extraction and fall classification. The CNN leverages its ability to automatically learn discriminative features from raw sensor data, enabling robust and accurate classification of fall and non-fall events. Experimental results demonstrate the efficacy of the proposed approach in accurately distinguishing between fall and non-fall activities, achieving high classification performance metrics such as accuracy, precision, recall, and F1-score. Comparative analysis with existing methods showcases the WMA-CNN hybrid approach's superiority in classification accuracy and robustness. Overall, the proposed methodology presents a promising framework for real-time human fall classification using sensor data, offering potential applications in wearable devices, ambient assisted living systems, and healthcare monitoring technologies to enhance safety and well-being among elderly individuals.

Chicken nuggets with the addition of purple sweet potato puree and shrimp are innovative nuggets made from chicken meat, purple sweet potato, shrimp and spices. The experiment aimed to determine: 1) the best sensory test quality: 2) nutritional content, namely Protein, Fat, Carbohydrate, Antioxidant, Fiber; and 3) selling price  250 grams.  research method used experiments to conduct 2 trials to determine  best sensory test. Data collection techniques through sensory tests using instrument 30 panelists. Data analysis technique with quantitative descriptive analysis of percentages.  results showed: 1) color sensory test results 22 (69%) light purple, 8 (25%) purple and 2 (6%) not purple, shape 16 (53%) love-shaped, 14 (47%) less perfect, aroma 21 (70%) smells combination of chicken and purple sweet potato, 7 (23%)  combination of chicken and shrimp, 2 (7%) less flavorful shrimp and purple sweet potato, taste 20 (67%) moderately savory combination of chicken shrimp  little sweetness purple sweet potato, 9 (30%) savory combination of chicken, shrimp, 2 (3%) sweet not savory purple sweet potato. Texture 18 (60%) soft chewy solid 12 (40%) solid; 2) laboratory test results content per 100 grams; Protein 12.83%, Carbohydrate 36.56%, Fat 6.05%, Antioxidant 92.88%, Fiber 3.22%; 3) Selling price 250 grams IDR 36.800.

Red bean flour has a high protein content but low gluten content. The superior nutritional value of rice bran is as a nutrient source that contains a lot of protein and high fiber and also does not cause allergies. The purpose of this study was to determine the effect of roasting time and the best formulation of the combination of red bean flour and rice bran flour in making snack bars that are rich in protein and favored by many consumers. This study used a completely randomized design (CRD) arranged factorially with two factors with the formulation of red bean flour and rice bran flour used were P1 (95:5); P2 (90:10); and P3 (85:15). Roasting time was 50, 40 and 30 minutes. Data analysis used ANOVA with Tukey's further test. The results of chemical and sensory tests significantly influenced the activity of water content, fat content, protein, carbohydrates, color, red bean flavor, bran flavor, hardness and overall liking. However, it was significantly different for ash content, color and overall liking. The best chemical test results were P2T3 (ratio of red bean flour and rice bran flour 90/10 with roasting time of 30 minutes) with the results of carbohydrate 60.74%, protein 10.96%, moisture content 19.01%, fat content 6.79%, and ash content 2.51%. The best sensory test results were P2T3 with color test results 2.98, red bean flavor 2.58, bran flavor 2.32, hardness 1.75, and overall liking 2.77. Snack bars made from red bean flour and rice bran flour have great potential as a high-protein food ingredient.

Red rose (Rosa damascena Mill) is one of the plant that can be easily found in Indonesia. The corolla of red roses contains natural dyes, namely anthocyanins which can be used as food coloring and the function as antioxidants or counteract free radicals. The corrola of red roses is used as a raw material in distillation of rose water. Rose water distillation poduces is a dark red liquid. This liquid waste has not been utilized optimally. Therefore, that further research is needed to determine the chemical content in it. So that the expected outcome of this research is the best chemical and sensory analysis of red rose water distillation waste based on it's antioxidant activity. The research design used a 2 factor factorial completely randomized design (CRD). The first factor is the variation of the distillation method while the second factor is the heating temperature of the red rose water waste (heated waste). The optimal treatment result was a combination of steam distillation method variations and 70°C heating temperature with following results obtained : 77,32% RSH DPPH, 61,02% FRAP value, 71,20 mg/g vitamin C, 4,58 mg  total phenol.GAE/ g, pH 4,15, anthocyanin 121,93 mg/g, brightness 27,23 (*L), red-green chromatic 7,13 (*a), blue-yellow chromatic 7,54 (*b). Sensory analysis of color was 4.36 (deep red), other scents were 2.47 (slightly sour), rose aroma was 3.64 (strong), and overall preference was 3.75 (liked).

Burglary involves forced or unauthorized entry, which leads to damage or loss of property having monetary or emotional value and, more severely, puts lives at risk. The dire need for the safety of lives and properties has attracted so much research on burglary alert system using Internet of Things (IoT) technology. Most of the research focused on alerting the users of burglary attempts using any or a combination of two notification methods: SMS, call, and email. This study emphasizes three-mode notification that combines SMS, call, and email using the application of IoT technology in a burglary alert system, which uses a Passive Infrared (PIR) sensor for burglar detection to ensure that Homeowners or authorized personnel get alerts in events of imminent attempt to break-ins. The study also details the sensor integration with its supporting components, such as the central hub or microcontroller, buzzer, LED, and network interface in the development of the system. The software was developed to facilitate seamless integration with the hardware, ensuring timely and accurate event detection and subsequent alert generation using Arduino IDE programming language, a framework based on the C++ language. The system effected the 3-mode notification to ensure that users get notification in case of an imminent break-in since the failure of the three modes simultaneously is extremely rare. The system’s performance based on its responsiveness on the 3-mode notifications was evaluated, and an average of 83.56% responsiveness was obtained, indicating an acceptable response time.

Renewable energy microgrids integrated with smart control systems are emerging as a sustainable solution for electrifying rural industrial zones, offering substantial improvements in energy efficiency and reductions in carbon emissions. This study explores the implementation of hybrid renewable energy systems, combining solar and wind energy, and the integration of Internet of Things (IoT) sensors to optimize energy consumption in real-time. The findings highlight that the combination of solar and wind energy in microgrids leads to up to a 30% increase in energy efficiency, with a significant reduction in CO₂ emissions, reaching up to 50% compared to traditional grid systems. IoT sensors play a crucial role in load forecasting, optimization, and system stability, enabling real-time monitoring and proactive adjustments to energy distribution. Additionally, the implementation of these systems in rural industrial zones not only provides reliable, clean energy but also reduces reliance on fossil fuels, making them economically viable and environmentally sustainable. However, challenges such as high initial investment costs, integration complexities, and the need for skilled technicians remain. Despite these barriers, the long-term benefits of reduced energy costs, improved energy security, and lower carbon footprints make renewable energy microgrids a promising solution. The study suggests that these systems can be scaled to other rural regions facing similar challenges in energy access and carbon emissions, offering a path to sustainable development. Further research is recommended to explore alternative renewable energy combinations and advancements in IoT applications to improve system scalability and efficiency.