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Manual quality assessment of Platelet Concentrate (TC) is highly subjective and inconsistent, necessitating an objective, automated classification system. This study aims to develop a computationally efficient, low-cost model for TC quality classification using Histogram Features extracted from grayscale images combined with the K-Nearest Neighbor (KNN) algorithm. The methodology employed critical preprocessing steps, including StandardScaler for normalization and SMOTE for balancing the training data, followed by optimization across K=1 to K=30. The optimal model achieved a maximum accuracy of 69.23% at K=6, with an F1-Score of 71.43%, confirming robust performance on the imbalanced testing set. The results validate the effectiveness of the Histogram-KNN approach as a consistent and reliable decision support system for rapid TC quality screening in resource-limited settings.

The development of renewable energy, particularly Solar Power Plants (PV), requires a reliable, real-time, and easily accessible electrical energy monitoring system to ensure optimal system performance. This study aims to design and implement an Internet of Things (IoT)-based electrical energy monitoring system for PV using the NodeMCU ESP32 microcontroller, the PZEM-004T sensor for measuring electrical parameters, and the Node-RED platform as the data visualization interface. The developed system is designed to monitor voltage, current, power, energy, frequency, and power loss in real time, and then display the data in the form of numerical values, graphs, and indicators on a dashboard accessible through a local network. The research method includes hardware design, software development (sensor reading, data processing, and communication), integration with Node-RED, and system testing on a small-scale PV installation. The test results show that the system is capable of monitoring electrical parameters in a stable and responsive manner. Variations in sunlight intensity were found to affect the current and power produced by the solar panels, whereas the inverter output voltage tended to remain within normal operating ranges. The Node-RED dashboard display was considered informative and helpful for users in monitoring and analyzing PV performance. Based on these results, it can be concluded that the IoT-based electrical energy monitoring system designed in this study functions well and is feasible for application in residential or educational-scale PV installations. The system still has the potential for further development through cloud service integration, the addition of environmental sensors, and enhancements to data analysis features and user interface design.

Waste has become a serious environmental problem in Indonesia, which continues to increase along with population growth. The issue of waste management poses serious challenges for the environment, especially in the process of separating organic and inorganic waste. In the field of computer vision, recognising the type and shape of waste through camera images remains a challenge due to variations in shape, colour, and complex lighting conditions. Therefore, this problem utilises Deep Learning technology, which is expected to be widely applied in Indonesia, especially in large cities with high waste volumes. This study aims to distinguish between organic and inorganic waste using the Convolutional Neural Network (CNN) method based on digital images. The developed CNN model was trained to recognise the visual patterns of each type of waste and tested to measure its accuracy. The test results show that the CNN-based classification system is capable of achieving an accuracy rate of 95%, thus proving the effectiveness of this method in supporting artificial intelligence-based automatic waste sorting systems.

Oxygen is vital therapy where delivery accuracy is crucial, especially for infant patients, to ensure treatment effectiveness and prevent the risks of hypoxia or toxicity. With the implementation of the mandatory Domestic Product Utilization Policy (TKDN+BMP ≥ 40%), evaluating the quality of local products has become an urgent necessity. This study aims to test and analyze the quality and accuracy of domestically produced infant oxygen flowmeters compared to an imported product. The method used was experimental testing, measuring three brands of domestic products and one brand of foreign product at flow rate settings of 0.5, 1, 1.5, and 2 liters per minute (LPM). Each setting point was measured 10 times using a standardized calibrator to ensure data reliability. The measurement results were analyzed to identify the deviation level of each product. The findings of this study are expected to provide an objective conclusion on the quality equivalence of domestic products with imported ones and to identify which product has the lowest deviation rate. This can serve as scientific consideration for hospitals in selecting high-quality infant oxygen flowmeters, thereby supporting the domestic product policy.

The advancement of information technology has had a significant impact across various sectors, including healthcare. The digitalization of healthcare services has become a solution to improve efficiency, effectiveness, and accessibility for the public. Puskesmas Selindung still uses a manual patient registration system, which leads to several issues such as long queues, extended waiting times, and the risk of lost or damaged patient records. Based on visit data, the number of patients coming to Puskesmas Selindung has increased each year. Therefore, a digital queue system is needed to optimize the patient registration process. This research aims to analyze and design an Android-based patient registration queue application to improve service efficiency at Puskesmas Selindung. The research methods include system requirements analysis, user interface design, and the development of core features to support the online patient registration process. The implementation of this application is expected to reduce long queues, speed up administrative processes, and make it easier for patients to access healthcare services more effectively and accurately. With this Android-based system, the quality of healthcare services at Puskesmas Selindung is expected to improve significantly.

The problems in rice fields are complex and varied, depending on geographic location, rice variety, and growing season. Pests often cause serious economic losses. The Solar Sonic Repeller is an innovative portable pest control device designed to address pest problems by utilizing renewable energy, specifically solar energy. This product aims to offer an environmentally friendly and efficient solution. It works by emitting ultrasonic sound waves with a frequency of 30,000–40,000 Hz. The device's advantages lie in its portability and energy independence, thanks to the use of a charging module powered by an integrated photovoltaic (PV) panel with automatic battery charging during the day. The first test measured the output frequency using an oscilloscope to verify that the oscillator circuit produced waves at the specified frequency. The second test measured the device's effectiveness by examining the pest response to the device at various distances. This test was effective within a maximum radius of approximately 14 m from the center point, covering a rice field area of ​​250 m2.

Mental health is a crucial aspect of modern life, with stress and anxiety being among the most common and impactful psychological disorders. This research proposes a stress and anxiety monitoring system based on the Internet of Things (IoT), integrating biometric sensors and Deep Neural Networks (DNN) for early detection and in-depth analysis. The system is designed using MAX30102 (heart rate and SpO₂), GSR (Galvanic Skin Response), and DS18B20 (body temperature) sensors, managed by an ESP32 microcontroller and communicating through the MQTT protocol. Physiological data is collected in real-time, formatted in JSON, and transmitted to both Android and web-based applications for visualization. The DNN model is developed using the TensorFlow framework with a layered architecture and ReLU activation functions to classify four mental states: relaxed, calm, anxious, and highly stressed. The training dataset comprises both primary and secondary data, including the WESAD dataset. Model performance is evaluated through k-fold cross-validation, showing high accuracy and strong generalization capabilities. The results indicate that the integration of sensor technology and deep learning significantly improves the effectiveness of stress and anxiety detection compared to traditional methods. This system demonstrates great potential for the development of AI-based wearable devices for autonomous, real-time, and adaptive mental health monitoring.

The insurance business in an insurance company offers insurance products owned by insurance companies. There are many transactions such as the purchase of insurance products and the application of disbursement of insurance benefits to customers, so that disputes occur in the reports generated every month and this does not become effective and time-efficient as needed. This study aims to evaluate the effectiveness of a website-based real-time insurance transaction reporting monitoring system. This research method involves the development of a web-based system designed to monitor and report insurance transactions directly, as well as the evaluation of system performance using quantitative and qualitative approaches. The research stages include needs analysis, system design and development, implementation, and system testing and evaluation in insurance companies. The results of the study show that a website-based system can facilitate evaluation Monitoring the results of reports on ongoing transactions, so that reports every month can be formed digitally through the system that has been created.  

This study examines the role of Artificial Intelligence (AI) in marketing strategy through a Systematic Literature Review (SLR) approach. AI has shown a transformative impact by outperforming traditional methods, especially in optimizing big data-based marketing strategies. With the ability to analyze consumer behavior in depth, AI enables businesses to personalize marketing efforts and improve user experiences more efficiently and responsively. However, challenges such as data privacy, high initial investment, and reliance on data quality remain major concerns that must be addressed. This study also evaluates the effectiveness of using AI across marketing channels, which shows significant differences in their impact on business strategy. In addition, the integration of AI-based fitness equipment is considered to have a major contribution in increasing consumer satisfaction while driving online business growth. The results of this study provide valuable insights into the effective implementation of AI, as well as highlight the importance of maintaining data security and implementing AI strategically to provide optimal benefits for consumers and business development.

Football School (SSB) is a supporting facility for children who have potential in the field of soccer in order to improve their skills. Football is a large ball game played in teams with a team of 10 players and 1 goalkeeper. In this game, teamwork is an important value that must be possessed to achieve competitive victory. However, along with problems in the form of discrepancies in operational standardization in soccer schools, causing negative public perceptions of the existence of this school. Therefore, a research was conducted to build a decision-making model in determining the choice of soccer schools in accordance with legal standards for children, namely using the Analytical Hierarchy Process (AHP) method. The AHP method is one method that can solve a problem because there is a hierarchy where there are several important aspects, namely Objects, Criteria, Sub Criteria, and Alternatives. By combining data and knowledge, it can increase effectiveness in decision makers. It is hoped that in the future, this research can help the community to support their children in the field of soccer by determining the appropriate soccer school.

By looking at current technological developments that already use automatic sensors, the application of the concept to this system can be a solution for dealing with ornamental fish farming owners. In this research, a tool is made that can perform feeding, checking temperature, water turbidity, feed level, water level and water pump control, from this information will be sent to android by firebase automatically monitored and controlled anywhere via android. This tool is designed with ease of maintenance and is an extension of the existing tools. IoT technology is used to monitor online, based on Firebase and Nodemcu Esp8266. In this study, researchers used the research method of the Borg and Gall (1987) model from 10 steps to 6 steps. The results of this study were carried out by an expert validation test to get a value of 30 which means "Very Good (Valid)". While the effectiveness test by 10 users plus by experts and employee users get a total score of 35.16 which means the effectiveness test is classified as "Very Good (Valid)" it can be said that the new system is more effective than the old system.

Starting from the development of medical technology that is increasingly sophisticated and rapidly growing,researchers conduct medical research, namely about patient infusion handling services. In handling patient infusion, currently it is still manual which is carried out by nurses / medical personnel. Infusion handling services for patients still have shortcomings, namely the process of monitoring and replacing infusion fluids which are often late. If the problem is not treated quickly, it can lead to problems, namely the presence of air embolism in the blood vessels (the entry of foreign objects into the blood vessels, for example air). From that problem, the researchers made a new innovation in medical technology in handling infusions automatically and based on IoT. In this study, the smart online infusion device that has been made has good features and is very effective in handling infusions. This device has 3 main functions, namely: it can monitor the remaining infusion, it can change the infusion fluid automatically and it can indicate a blocked patient's infusion. This device already has a method for processing data with fuzzy logic. Media monitoring has been supported by a website that can be controlled remotely and in real time. Tests have been carried out and the effectiveness of the system is found to have an error rate of 0.2% - 0.7% and has an accuracy of 98%. Thus this tool can be used in terms of handling patient infusion automatically.

At the present time of the pandemic, it is difficult for the world's most unusual cuttlefish to market its products. Thus, umkm needs to be provided with facilities to market the products online. Special-based backends are one of the media for selling by-products on the catapult. The purpose of this research is to construct typical web-based appendage by-by-products. The purpose of this research is to construct typical web-based appendage by-by-products. Research methods used in the construction of systems on this research are the methods of research and development (R & D). This study provides several design systems, the design of system architecture, the DFD system, the design of the interface, and the design of system testing. The system was created using the framework laravel. As for the results of the final assignment research "typical web-based appendage". In this system, there are two users, the user as the store and the user as the buyer. On the user as a store there are several features that include input from store products, editing from products, confirmation of deliveries, responding to comments given by the buyer on the product, viewing the order data done by the buyer, and editing the store's data. While the user's features as the purchaser look at the product's data, see the store's data as a souvenir, order a by-product payment, confirm the order has been accepted, give an assessment of the product's already received, and edit the customer's data. The system was tested by using black box methods testing to see the effectiveness of a system built with test variables was 100%.

Diamond Printing is one of the largest offset printing companies with 32 years of experience and is located in the city of Surabaya, East Java. Data from HRD managers explained that there was no report from observations related to employee work effectiveness in terms of coordination and synergy between employees as seen from the communication and collaboration relationships. The absence of data related to the effectiveness of the performance of CV employees. Diamond Printing in terms of communication network mapping is one of the obstacles faced by HRD in determining KPI (key performance indicator). By using the Social Network Analysis (SNA) method with the help of UCINET 6 software, it is hoped that some employees will have advantages, especially in collaboration and communication in group network structures. There are three parameters used in SNA, including: degree centrality, closeness centrality, and betweenness centrality. This study involved 104 respondents (the entire population) with a sampling technique using snowball sampling and a questionnaire as a means of collecting data. The results of this study indicate that most of the collaboration and communication network interactions are dominated by manager level employees and department heads. Based on these findings, an innovation is needed from all stakeholders from CV. Diamond Printing in developing effective communication methods between its members.

The use of information, media and communication technology has changed both the behavior of society and human civilization globally. The development of hospitals in Karawang is increasingly mushrooming, as well as the increasing number of degenerative diseases such as hypertension and diabetes, the increasing prevalence of chronic kidney disease. So it requires the handling of renal replacement therapy (Renal Replacement Therapy) because it is increasingly needed for cases of acute and chronic renal failure. The purpose of this research is to build an integrated and controlled information system that can simplify the patient administration process and reduce the effectiveness of the patient's time for dialysis. The methodology that the authors use in this study includes methods of identification and system design. System identification includes identification of the organization, running systems, and problem identification. The problems faced at this time in the Hemodialysis Installation. Patient data is not the same between patients who are served by hemodialysis (dialysis) and those in the application report, the transaction value for using tools and materials is sometimes empty or there is no transaction value in the application, it will cause losses to the customer. hospital. It is hoped that this system can eliminate the problems that have been happening so far.

The management of production and operations in factory machinery is an optimal management effort in the use of resources consisting of labor, machinery, equipment and raw materials. The production and operations manager directs various inputs in order to produce various outputs or results in units of quantity, quality, price, specific time and location according to consumer demand. Efficiency and effectiveness of the production process to be achieved requires proper scheduling management so that the production output produced can be completed according to target. Management of production and customer orders is still simple, besides that the status of raw material inventories that cannot be directly known can often result in delays in the production process and even production cannot be done as soon as possible. Scheduling orders that enter using the system first in first out where the first order that comes is done, but has not considered the number of orders, priority of customers, maturity of workmanship and engine capacity so that the estimated completion of the order can not be known. To make it more efficient and directed, the Earliest Due Date method is used by sorting the production work based on the closest due date. This method can be used for scheduling on one machine or for scheduling on several machines (parallel machine) so that the scheduling management information system can manage effective production scheduling and produce production reports automatically as needed.

PT. Vermindo Utama Semarang having its address at Jl. Pawiyatan Luhur Number 25 Semarang is a company engaged in the distribution and production of goods, especially health products. PT. Vermindo Utama Semarang has dozens of Salesmen and a leader. PT. Vermindo Utama Semarang carries out the process of buying and selling wholesale with various customers, the majority of whom are Pharmacies and supermarkets. In running its business, PT. Vermindo Utama Semarang still sells conventionally by using salesmen. And the marketing area still covers Central Java and East Java. Based on the problems above, the writer wants to propose a web-based booking system design to be considered in helping in the promotion of goods from PT. Vermindo Utama Semarang. Application Order System PT. Vermindo Utama Semarang by using PHP and MySql database. Making this application is expected to be one of the efforts that can be done to overcome the problems that often occur so as to increase the effectiveness of work which will certainly affect the quality of service to customers.