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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.

Eclairs are cakes that are much favored by the general public, became as éclair a hollow texture and are soft on the inside. Mocaf is flour has been modified by fermentation, and has characteristics similar to wheat flour. This reseacrh used a variety of peanuts flour such as cowpeas, red bens and mung beans as protein and fiber source. The variety of nuts added aims to encrease the nutritional content of eclairs. This research was purposed to determine the chemical and sensory characteristics of eclairs which are high in protein and fiber and to determine consumer preferences from the comparison of mocaf and wheat flour with various types of peanut flour. The experimental design used was a Completely Randomized Design (CRD) with two factors, the first factor was the ratio of mocaf flour and wheat flour 9:1, 8:2, 7:3, the second factor was the variety of species of beans, cowpeas, red beans, mung beans. The results showed that the protein content was the highest, in the mocaf and wheat flour of 7:3 with a protein content of 8.50%. the eclairs formulation with the highest fiber content was found in a 9:1 ratio of mocaf flour and wheat flour with variety types of mung beans flour with a fiber content of 9.94%. The formulation of the ratio of mocaf flour : wheat flour 7:3 with variety species is the most preferred formula overall with an overall preference level of 3.67. Eclairs with the addition of peanut flour has the potential to increase product protein.

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.

Vermicelli is an alternative food to replace rice, a type of noodle that is still in great demand by the public. Vermicelli is a popular food made from rice flour processed through an extrusion process so that it is shaped like a thread. The substitution of potato starch and the addition of celery extract will increase the antioxidant activity content of the vermicelli. The purpose of this research was produce vermicelli which has high antioxidant activity and produce vermicelli with characteristics according to Indonesian National Standard No. 01-2975-2006. Complete Randomized Design factorial with two factors were used in this research. The first factor was the ratio of rice flour and potatoes flour (10:90, 15:85, 20:80). The second factors was the levels of celery extract to water addition of dough (0,78; 1,04; 1,56%). The vermicelli were then tested for moisture content, ash content, crude fiber content and antioxidant activity as well as sensory analysis. The data analyse using Analysis of Variance (ANOVA). The best treatment was on ratio of substitution potatoes flour 20:80(g) with celery extract (0,78%). The fermicelli produced has the following characteristics water 10,65%, ash content 0,52%, fiber content 3,45% and 19,25% antioxidant activity. Femicelli produced in accordance with the quality requirements of SNI No. 01- 2975-2006. The sensory test of fermicelli that having color for dry fermicelli (3,82) color is yellowish dark green, color for wet fermicelli (3.62) is slightly faded green, texture (2,68) is not chewy, after taste (3.36) the taste of celery that lingers after being swallowed and overall preference (3,42).

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).

Today's people tend to consume healthy food, for example, functional food. Functional foods from fermented milk products which contain many bioactive compounds include yogurt, kefir, and cheese. The nutritional value of this product can be further increased through fortification of various types of tea. This research aims to summarize results related to the fortification of various types of tea in yogurt, kefir, and cheese products as a functional food innovation based on fermented milk. Based on various research, tea fortification in fermented milk products can increase the functional value of the product. Fortification of green tea, oolong tea, white tea, and black tea as much as 0.5 – 4% has been proven to increase the total phenolic content, antioxidant activity, antimicrobial and LAB growth as well as produce better color, texture, and sensory properties of yogurt. Green tea and black tea fortification of 1 – 4% is also believed to produce kefir with better antimicrobial and antioxidant activity and has a lower calorific value than products without tea fortification. Cheese with green tea or orthodox black tea fortification of 0.1 – 2% or 2 g/kg has been proven to be able to enrich polyphenolic compounds up to 2 times, and the antiradical activity of the cheese is up to 44%, and the antioxidant activity of the cheese is 14% higher than the control. Based on the research that has been carried out, it is believed that the fortification of various types of tea in yogurt, kefir, and cheese products can be an innovation in the development of functional food which can have a better impact on body health.

The cereal products available in the market mostly focus only on practicality and ignore the nutritional content. It is necessary to increase the nutritional content of these products by using local Indonesian raw materials such as sweet potatoes and corn.  The objectives of this study are: 1) to determine the effect of temperature and proportion of purple sweet potato flour and corn flour on the characteristics of cereals produced, 2) to assess the level of preference of panelists for the physical, chemical and sensory qualities of cereals produced. The study design used a factorial randomized design complete with a proportion treatment of purple sweet potato flour and corn. Test parameters include water content, degree of swelling, water absorption, texture, antioxidants, and sensory evaluation. The conclusion in this study is that the comparative treatment of purple sweet potato flour and corn and temperature did not have a real effect on water content, degree of development, water absorption index (IPA), water solubility index (IKA), texture and antioxidants but had an effect on sensory properties

An Internet of Things (IoT)-based logistics monitoring system is an innovation designed to enhance efficiency, transparency, and speed in supply chain management. The implementation of IoT in logistics provides an ideal solution for real-time monitoring of goods, which was previously difficult with conventional methods. This system integrates IoT sensors such as GPS for location tracking, along with temperature and humidity sensors to monitor goods requiring special attention, such as food and pharmaceuticals. By automating processes through IoT technology, goods distribution becomes faster, reducing reliance on manual controls, speeding up decision-making, and minimising human error. This system enables companies to monitor the condition and location of goods in real-time, offering high visibility into the logistics status. With comprehensive monitoring, companies can proactively address issues and ensure goods remain in optimal condition throughout the shipping process. An IoT-based logistics monitoring system has the potential to enhance a company’s competitiveness through efficiency and accuracy in supply chain management. When effectively implemented, IoT technology can not only improve service quality and customer satisfaction but also strengthen a company’s position in an increasingly competitive market.

This study seeks to create a system for monitoring the environment using the Internet of Things. It aims to help farmers manage their rice fields in a way that is both effective and sustainable. The system will provide farmers with real-time data on soil moisture, air temperature, and rainfall, allowing them to make informed decisions. Sensors will collect this information, which will be analyzed and presented simply through a web or mobile app. Early simulations suggest that this system could boost crop yields by as much as 15% and cut water use and costs by 20%. These findings point to the IoT monitoring system as a practical means to enhance rice farming's efficiency and productivity. Yet, there are hurdles. Issues like poor network infrastructure, high costs of implementation, and the farmers' ability to adapt to this technology need to be overcome for the system to work properly. This study aspires to make a real difference in promoting sustainable farming practices while paving the way for more advanced IoT solutions in the future.

Energy efficiency is a critical concern in wireless sensor networks (WSNs) due to the limited power resources available in sensor nodes. Prolonging network lifespan while ensuring reliable data transmission is essential for successful deployment in various applications, such as environmental monitoring, military operations, and industrial automation. This paper presents a mathematical model designed to optimize energy consumption across various nodes in WSNs. By implementing simulations and analyzing data from these models, the study demonstrates significant improvements in extending network lifespan while maintaining reliable data throughput. The findings contribute valuable insights into energy management for large-scale sensor deployments.

Cyber Physical Systems (CPS) are vital for managing and controlling critical infrastructures, such as industrial control systems, power grids, and transportation networks. These systems integrate digital and physical components, offering numerous benefits for industrial automation. However, the increasing interconnectivity of these systems has introduced new security vulnerabilities, particularly in anomaly detection and system reliability. This research aims to address these challenges by proposing an edge based anomaly detection framework that leverages lightweight deep learning models, specifically designed to operate efficiently on resource constrained edge devices. Literature Review: Previous studies have shown the effectiveness of anomaly detection in CPS, with traditional methods struggling to keep up with the complexity and scale of modern industrial environments. Machine learning and deep learning approaches, particularly hybrid models combining rule based systems and AI, have emerged as effective solutions for real time anomaly detection. Techniques such as model compression, quantization, and pruning are essential for adapting these models to resource limited edge devices while maintaining high detection accuracy and low latency. Materials and Method: The proposed framework integrates deep learning models such as Convolutional Neural Networks (CNNs) and Long Short Term Memory (LSTM) networks, optimized for edge computing environments. The datasets used for training and testing include industrial network traffic and sensor anomaly datasets. Model optimization techniques like pruning and quantization were applied to reduce computational overhead and energy consumption on edge devices. Results and Discussion: The framework demonstrated high detection accuracy (AUC of 0.9720) with ultra low latency (0.0019 seconds training time), making it highly suitable for real time anomaly detection in CPS. Resource efficiency was achieved by optimizing the models for edge devices, reducing energy consumption while maintaining performance. The framework also significantly improved security by identifying anomalies early, preventing potential threats to critical infrastructures. Future directions include exploring federated learning to enhance privacy and data sharing across distributed devices.

Monitoring the growth and development of a child can begin from conception and will continue until adulthood, this process is mutually continuous and continuous. The development of language skills, creativity, emotional awareness, and intelligence is an important phase in a child's growth and development and is the cornerstone of subsequent development. This study aims to evaluate the ability of early childhood to improve gross motor and fine motor development skills through sensory play activities. The method of delivering information using the media of story books (fairy tales), sensory game tools that previously the children were given directions one example of simulation, then the children were directed to do independently. the results of normative identification of children's growth and development, it can be seen that from the value (5-1) range always to never, overall participants play with the highest frequency in the range is always on the cognitive and social interaction, the second position in fine & gross motor skills, and third in terms of language development and problem solving skills. The highest score level after the game, cognitive development is very significant children are very enthusiastic to follow the game conducted in groups. This activity will be better if done on an ongoing basis because it is very beneficial for early childhood development.

Snack bars are processed food products that shaped rectangular or like a bar. Snack bar in this study used ingredients of barley flour and mocaf. Barley is a potential ingredient as a source of dietary fiber and gluten-free mocaf can fix the texture of barley. One of the factors that affects the quality of the snack bar is the baking process. The purpose of this study was to determine the effect of temperature and baking time on the characteristics of physical, chemical, and sensory of the snack bar, and to determine best formulation of the temperature and baking time of the snack bar. The design applied was a completely randomized design with two factors consisting baking temperature of 130 and 160°C, and baking time of 20 minutes and 40 minutes. The results showed that baking time had a significant effect on the values of a and b, but not significant on the value of L. Baking temperature and time had a significant effect on the level of preference for texture, color, overall and on texture and color on sensory quality. However, it had no significant effect on aroma and taste. The baking temperature had a significant effect on the moisture content, but roasting time had no significant effect. The best snack bar was that baked at 160ºC, 20 minutes. The best formulation of snack bar contains nutrients, water content of 15%, ash of 1.906%, fat 19.447%, protein 21.012%, carbohydrates 42.635%, dietary fiber 11.262% and total calories 429 kcal.

Katte tong arrowroot-wheat flour has potential functional food that can be developed to optimize local ingredients. The addition of white saffron powder and CMC, which believed to provide health benefits because has high antioxidant activity and improve the texture to be sturdy. The purpose of this study was to determine the effect of the addition of white saffron powder and CMC on the physical, chemical and level of liking of katte tong arrowroot. This research was conducted to make katte tong with arrowroot-wheat flour with the addition of white saffron powder and CMC using a two-factorial completely randomized design (CRD). Factors included the addition of white saffron powder at 5, 10, 15% and CMC at 0.5, 1, 1.5%. Katte tong garut was then tested physically, chemically, and tested for favorability. The results showed that the addition of white saffron powder and CMC had a significant effect on the physical and chemical properties and preference level of the katte tong produced. The results of the analysis of the selected arrowroot katte tong have a moisture content of 1.82%bb, protein 7.89%bb, antioxidant activity of DPPH method 22.65% RSA, antioxidant activity of FRAP method 3.6 mg Efero/g and total phenols content 11.41 mg EAG/g.

This Space Security System is a system that utilizes the existing Internet Network to monitor a room remotely or from a different location. With the aim of making it easier to limit employee access rights and monitor the presence of people in the room.So the author made a room security system tool using the Internet of Things (IOT) which was implemented at the Demak Regency Communication and Information Service. The way this system works is only employees who have access rights who can enter the room by attaching an RFID card to the RFID Reader sensor, and the way the PIR sensor works is to monitor human presence, when there is infrared or human emission it will send data to the web if it is in the room has people and the red LED lights up and the buzzer sounds, while the push button button is when the push button button is pressed the solenoid will open. By making this design, it will help improve room security at the Demak Regency Communication and Information Service, especially the Encryption Room

Sensory Integration Therapy is an approach that focuses on sensory stimulation to improve sensory processing and adaptive responses in individuals with sensory disorders, one of which is children with autism. Sensory integration therapy makes it easier for autistic children to communicate to be better understood and to create good social interactions. Therefore, the Yasmin Autism Therapy Center carries out Sensory Integration Therapy to improve social interaction in autistic children. This research aims to determine the application of sensory integration therapy at the Yasmin Autism Therapy Center to improve social interaction in autistic children and determine the obstacles in implementing sensory integration therapy. Data collection techniques include documentation, observation and interviews. The results of the research show that the stages of Sensory Integration Therapy at the Yasmin Autism Therapy Center are providing simple instructions, a series of sequential activities and honing concentration, consistency and endurance in activities through play. Supporting factors for sensory therapy activities include good collaboration between therapists and parents. Meanwhile, the obstacles to children's communication are difficult factors, limited therapy tools, and limited therapy time.

Babies have three needs that must be met by parents, namely physical-biological needs which are useful for brain growth, sensory systems and motor skills. Interpersonal and intrapersonal emotional intelligence through the need for affection, as well as the need for stimulus or stimulation to improve the working mechanisms of the sensory and motor systems. The most important thing in a child's growth and development is stimulation (Maharani, 2017). This study aims to analyze the effect of baby massage on weight gain in babies aged 3-6 months at the Uluan Community Health Center, Toba Regency in 2023. In this research, researchers used a quasi-experiment with a non-equivalent control group design to compare the results of health program interventions. in a similar control, but not necessarily the same group (Zulkarnain, 2018) Statistical test using Microsoft Excel and Paired Test to test differences in dependent data (dependent samples). The error rate or significance level (a) used is 0.05 with a confidence interval (CI) of 95% (Hardani, 2020). Based on the research results. Based on the results of statistical tests using Chi-Square, it was obtained that Based on the results of statistical tests using the paired t test, t = 6.610. Because t count (6.610) > t table (2.0345), HO is rejected and Ha is accepted. This shows that there is an influence of baby massage on increasing postpartum mothers regarding breast care with smooth breast milk production in Jatimulyo Village, Serdang Bedagai Regency in 2023

The rapid urbanization and industrialization of cities have significantly contributed to the rising pollution levels, especially in urban rivers, where water quality is often compromised. Monitoring water quality in real-time is essential for mitigating the adverse effects of water contamination. This research aims to design and implement an Internet of Things (IoT)-based system for real-time monitoring of water quality in urban rivers, focusing on the continuous collection and analysis of environmental data. The system utilizes a range of sensors to measure critical water quality parameters, including pH, temperature, dissolved oxygen (DO), turbidity, and various contaminants, all of which transmit data wirelessly to a central server for further processing. The study evaluates the accuracy, reliability, and efficiency of the IoT system in detecting water pollution and its ability to deliver real-time insights. Findings demonstrate that the IoT system offers a higher level of precision and faster detection compared to conventional monitoring methods, making it an effective tool for real-time pollution detection and decision-making. Additionally, the integration of the IoT system with a user-friendly visualization platform enhances the accessibility of the data for stakeholders, enabling them to monitor the water quality effectively. The study suggests that IoT-based water quality monitoring systems present a sustainable long-term solution for urban water management, offering cost and time savings. Moreover, the research highlights the importance of cross-sector collaboration to support the development and deployment of IoT technologies and recommends further advancements in sensor technologies to monitor additional water quality parameters.  

The rapid spread of infectious diseases remains a major global health threat, and early detection is vital to minimize their impact. This research investigates the role of predictive modeling using big data in the early detection of infectious disease outbreaks. The primary objective of this study is to assess the effectiveness of big data systems in forecasting potential outbreaks and the implications of these forecasts for public health systems. The study employs machine learning-based predictive models to process large health datasets, including electronic health records, sensor data, and social media information. The results demonstrate that the predictive model achieved an accuracy rate of 87%, significantly surpassing traditional methods in terms of early detection. By integrating various data sources such as medical records, sensor networks, and real-time digital traces, the system is capable of providing more accurate, timely predictions, which can greatly improve the ability of public health authorities to respond effectively to emerging health threats. Furthermore, the application of big data in public health not only improves the speed of response but also enhances the allocation of resources, allowing for more targeted and efficient interventions. Despite these successes, challenges remain, particularly in relation to data quality, privacy, and regulatory issues, which could hinder the broader implementation of such systems. Thus, collaboration between government agencies, healthcare institutions, and technology developers is essential to overcome these obstacles and ensure the sustainable integration of big data into public health infrastructures. This research highlights the significant potential of big data to transform public health responses, offering valuable insights for future epidemic management strategies.  

The chemical characteristics and sensory attributes of Robusta coffee are influenced by the environment of the coffee plant grows, one of the influencing factors is the altitude plantation locations. The aim of the research was to determine the effect of the land altitude of plantation location on the physicalchemical properties and sensory taste of Robusta coffee. This research used a Completely Randomized Design (CRD) with four (4) treatments based on altitude  of the Robusta coffee plantation were: 650; 750; 379 and 545 above sea level. The parameters observed in this study were  water content, ash content, pH value,  caffeine content, and sensory characteristics (fragance, flavor, after taste, colour and overall). Data were analyzed using Analysis of Variance (ANOVA). The ANOVA result shows the Duncan’s Multiple Range Test (DMRT). Data was processed using the SPSS version 26 program. The results of the research show that altitude of plantation has a significant effect on the pH value, water content, caffeine content and are not significantly different. from the ash content. The caffeine content shows real differences between on altitude of planting, the highest caffeine content is shown in Robusta coffee grown at an altitude of 650 m above sea level at 2.49% and the lowest in Robusta coffee planted at an altitude of 545 m above sea level, at 1,77%. The robusta coffee taste sensory test showed that Robusta coffee grown at an altitude of 650 m above sea level was the most delicious coffee.