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Accurate rainfall prediction is needed to improve the performance of land that always uses rainfall data. Data mining or often called knowledge discovery in databases (KDD) is an activity that includes collecting, using historical data to find regularities, patterns or relationships in large data. In predicting rainfall, there are several conditions that can be observed as reference data to predict rainfall, namely wind speed, temperature, and air humidity. In this research, a backpropagation artificial neural network prediction method is developed that can be used in predicting future rainfall. The backpropogation artificial neural network method that was built produced an accuracy value of 95.36%, a precision value of 90.50%, a recall value of 97.50% and an f-measure value of 92.00%

PT Aaron Innovation is a company that focuses on marketing yummys mother and child products, such as breast milk, maternity food, and baby skincare. With the wider reach of consumers through the TikTok platform, the company faces the challenge of increasing product return rates. This study aims to optimize the product return process at PT Aaron Innovation by identifying and implementing strategies that can increase operational efficiency, reduce costs, speed up and improve the accuracy of return handling, and increase customer satisfaction. This study uses a descriptive qualitative approach with a survey method, collecting data through direct observation and interviews with sources. The results showed that the current returns system is not optimal, with ineffective SOPs and a lack of special areas for returns handling, causing delays and irregularities in handling returned products.

Evaluation of SMILE in Data and Information Management (Case Study of BPJS Employment, Tanjung Morawa Branch) Using the User Compatibility Method. Effective data and information management in financial institutions such as BPJS Employment requires an application system that meets user needs. This research aims to evaluate SMILE at the Tanjung Morawa BPJS Employment Branch using the User Compatibility method, which assesses the extent to which the application meets the user's needs, abilities and expectations. This research method involves a survey of SMILE users at BPJS Employment Tanjung Morawa Branch, taking into account aspects of usability, efficiency and user satisfaction. Data was collected through questionnaires, interviews and direct observation of smile users. The evaluation results show that SMILE at BPJS Employment Tanjung Morawa Branch has a high level of compatibility with users. The research results show that all EUCS independent variables (indicators), consisting of Content (Content), Format (report), Accurancy (accuracy), Timeliness (speed of presentation), Ease of Use (easy to use), which have a significant relationship with user satisfaction SMILE. Users find this application easy to use, improves work efficiency, and meets their expectations regarding data and information management. However, several recommendations for improvement were also put forward, including increased training for users, improved integration with other systems, and improved data security. This study makes an important contribution to further understanding the extent to which SMILE meets user needs in internal environments. The evaluation results and recommendations produced can serve as guidelines for developing and improving smile in the future.    

The utilization of information and communication technology (ICT) in the management of educational institutions has become a key element of improving operational efficiency and effectiveness in the digital era. This study aims to investigate the role of ICT in data management, management, learning processes, and communication in educational environments. Using literature review techniques and secondary data analysis, this study found that the use of ICT increases information transparency, accuracy and speed, improving resource management and decision-making. However, ICT implementation also faces many challenges, such as infrastructure limitations, lack of technical capacity of human resources, and resistance to change. Overcoming these barriers requires a comprehensive and sustainable strategy. The results of this study are expected to provide insights to stakeholders in education regarding better management and optimization of ICT utilization to achieve quality education.unik.

Big data has revolutionized the landscape of natural sciences by providing extensive datasets that enable deeper insights and more accurate predictions. However, effectively analyzing such vast and complex data requires optimized machine learning algorithms tailored to specific applications. This study focuses on enhancing the performance of machine learning models in big data analysis for applications in natural sciences. The research aims to identify key optimization techniques, including feature selection, hyperparameter tuning, and algorithm customization, to improve model accuracy and computational efficiency. A combination of supervised and unsupervised learning approaches was applied to real-world datasets in fields such as climate science, genomics, and ecology. The findings demonstrate significant improvements in predictive accuracy and processing speed, highlighting the potential of optimized machine learning techniques in solving complex problems in natural sciences. The implications of this research extend to more efficient resource utilization and improved decision-making in scientific exploration and environmental management.

Quantum computing has emerged as a transformative technology with the potential to revolutionize numerical methods in scientific research. This study explores the integration of quantum algorithms to enhance the efficiency and accuracy of computational techniques used in solving complex scientific problems. The objective of this research is to investigate how quantum computing can address limitations in classical numerical methods, particularly in areas such as optimization, simulation, and data analysis. By employing quantum-enhanced algorithms, such as quantum Monte Carlo and quantum machine learning, the study demonstrates significant improvements in processing speed and solution quality. The findings highlight the capability of quantum computing to tackle challenges in high-dimensional computations and provide novel insights into scientific phenomena. These advancements have profound implications for disciplines ranging from physics and chemistry to material science and beyond, paving the way for a new era of computational-driven discoveries.

Stunting is a condition of failure to thrive in children, in Indonesia it is still a serious problem with a fairly high prevalence. The government is trying to reduce stunting rates with various health programs, and early detection through routine measurements is very important. This research uses the Extreme Gradient Boosting (XGBoost) algorithm to classify stunting status in children under five years. This study uses a relevant dataset containing anthropometric information on children, such as gender, age, birth weight and length, current weight and length, and breastfeeding status. The research stages include dataset search, preprocessing, classification, evaluation, and implementation in a local web-based prediction program. The XGBoost algorithm was chosen because of its advantages in speed, scalability, and efficiency. After preprocessing and data sharing, the model was trained and tested, resulting in 86% accuracy, 89% precision, 95% recall, and 92% F1-score. Evaluation using the confusion matrix and classification report shows that this model is quite effective in classifying stunting status.  

This research discusses the implementation and evaluation of the Convolutional Neural Network (CNN) convolutional neural network model for classification of fruit types, specifically to differentiate between Banana and Papaya. The CNN model used consists of several convolutional, pooling, and fully connected (dense) layers designed to extract features and perform binary classification. Data augmentation is applied to the training set to increase data variation and prevent overfitting. The image data used is normalized to speed up training convergence. The model was trained using the Adam optimizer and the binary crossentropy loss function for 20 epochs. Performance evaluation was carried out using the validation set. The results show that the model is able to effectively classify fruit images with a high level of accuracy. Predictions are made by uploading images, resizing them, and normalizing them before using the model for predictions. The classification threshold was set at 0.4, where a predicted probability greater than or equal to 0.4 was classified as Banana and a probability less than 0.4 was classified as Papaya. This research shows that the CNN model can be used effectively for binary image classification tasks and can be extended to classify more types of fruit with appropriate data adjustments and model architecture.

Fluent reading is the ability to master codes consisting of words by paying attention to the following factors: the ability to identify words automatically, the speed at which words move from one word to another, the procedures or expressions used in oral reading and accuracy. in translating the code to ensure the decoding process and understanding of the text being read. Therefore, the aim of this research is to analyze students' fluent reading abilities at level 2 in terms of reading accuracy and speed as well as fluency in reading texts with appropriate pauses, intonation and expression. The method used is a case study method through a reading test which is designed to assess the three main components of pauses, intonation and expression. The research subjects consisted of 3 2nd grade elementary school students|    

An employee payroll information system is an important component in an organization for managing employee salary data and payments effectively and efficiently. This research aims to analyze the factors that influence the success of employee payroll information system project management. The research method used is the waterfall method, which includes planning stages, needs analysis, system design, implementation, as well as testing and evaluation. This system is designed to automate the payroll process, from calculating salaries, withholding taxes, to creating financial reports. With this information system, it is hoped that it can reduce human error in the payroll process and increase employee satisfaction through transparency and accuracy of salary data. Where the implementation results show a significant increase in the speed and accuracy of payroll. Key factors for the success of this project include active involvement of stakeholders, use of appropriate technology, and effective risk management.

This research use the Naive Bayes algorithm to classification of user reviews of the Sky Childern Of The Light application from the Google Play Store. The Sky Childern Of The Light application is a popular online game, because it offers a unique and immersive playing experience. This method was chosen because of its simplicity, speed, ease of interpretation, and suitability for high-dimensional data. The advantages of Naive Bayes are the accuracy and efficiency of calculations, fast results and presentation. The data collected was 1500 data with a classification ratio of 8:2 with an accuracy value of 87% using the Naïve Bayes algorithm. This method is very good at analyzing the sentiment of the Sky Children Of The Light application.      

In the era of maritime technology, Unmanned Surface Vehicles (USVs) are becoming the main vehicles on the water surface, controlled from land and capable of transmitting live data. USVs have a wide range of survey and exploration applications, relying on hydrographic knowledge for accurate mapping. USV development has adopted a double hull design, improving stability and wave resistance. Survey data transmission requires advanced technology, with Long Range (LoRa) technology being the solution for long distance data transmission with low power consumption. LoRa utilisation is expected to increase the efficiency of USVs in hydrographic surveys. The research and development (R&D) research method is used as the main approach in this research with the aim of creating and developing USVs that can increase efficiency in hydrographic surveys. The USV is equipped with an RPM sensor and flowmeter used to monitor the movement control of the USV in the waters. In addition, a depth detector is used to monitor the topography of the seabed. In order for this USV to run using a remote control that is controlled from land. The USV drive consists of a BLDC motor connected to the propeller and a servo motor connected to the ship's rudder. Furthermore, the data taken from the sensor is sent via LoRa to be delivered to the ground station. From the USV test results, it was found that the data transmission range with LoRa Ra-02 under Line of sight (LOS) conditions was 340 metres while under Non Light of sight (NLOS) conditions it was around 200 metres. The average speed travelled by USV is 0.616 km/hour in operational survey conditions and can be faster in non-operational survey conditions. The error value of the RPM sensor is obtained at 1.604% with a reading accuracy of 98.936%.

This research aims to analyze the effectiveness of applying the case method to the reading comprehension abilities of 5th grade elementary school students using the case study method. The scanning reading technique is a reading method that focuses on quickly finding specific information in text. This research uses a case study approach to gain in-depth insight into the application of scanning reading techniques in grade 5 elementary school students. The research subjects were 5th grade elementary school students in Kampung Jati. Data was collected through observation, interviews, and reading comprehension tests before and after applying the scanning reading technique. The results of the research show that the application of scanning reading techniques among 5th grade elementary school students in Kampung Jati is still relatively low, especially in terms of reading speed and accuracy. This case study also reveals that students need to increase motivation and interest in reading activities.

As an important means of sea transportation for the distribution of goods and human mobility between islands, ships require a reliable prime mover to avoid wear or damage, especially when overspeeding occurs which can result in fire. Therefore, a prototype was created that uses an IR Obstacle sensor to monitor the RPM speed of the rotating engine. By using Arduino Uno as a processor, this prototype is able to display the RPM value on the LCD and provide a signal in the form of a green light if the speed is below 4000 Rpm, as well as a red light and buzzer sound if overspeed occurs above 4000 Rpm, followed by the engine turning off after 15 seconds. Testing shows that this prototype has a high level of accuracy, with a difference between 0.08% to 2.73% and an average difference of 1.003%.

Community Service in English means community service, which is an activity of helping the community in the form of several activities without expecting any form of reward. Community service is one of the pillars of the Tri Dharma of Higher Education, namely: education, research and community service. Universities not only carry out education for their students, but also carry out research and develop innovation, as well as preserve and develop superior knowledge that is beneficial to society. Data collection on marriages that have not been registered is a problem that is often faced in managing population data in many sub-districts. This article discusses the proposed solution through the development of the Kalimasada application to improve the quality of population data in Kedungdoro Village. The service method used involves the process of data collection, needs analysis, application development, and user training. The approach used is the use of mobile application-based information technology to facilitate the process of collecting data on unregistered marriages. The Kalimasada application is designed with an intuitive and easy-to-use interface, allowing sub-district officials to quickly record data on unregistered marriages. In addition, this application is equipped with an automatic data validation feature to reduce input errors and increase data accuracy. During the service process, training was conducted for the community about the importance of reporting unregistered marriages to subdistrict officers via the Kalimasada application. The results of implementing the Kalimasada application show a significant increase in data collection on unregistered marriages in Kedungdoro Village. With this application, the data collection process becomes more efficient and accurate, producing more valid and reliable data. Apart from that, public participation in reporting unregistered marriages has also increased, so that the data collected becomes more complete. In conclusion, developing the Kalimasada application is an effective solution for improving the quality of population data in Kedungdoro Village. The use of information technology in public administration can help speed up the data collection process and increase data accuracy. The next step is to expand the implementation of this application to other sub-districts and continue to carry out monitoring and evaluation to ensure its sustainability and effectiveness in the long term.

Applying ergonomic principles in work tool design for manufacturing industries is a crucial factor in improving productivity while maintaining worker health. This research aims to analyze the effectiveness of adaptive work tool design models based on cognitive and physiological ergonomic principles, identify interaction patterns between workstation design and operational performance, and develop a conceptual framework for integrating ergonomic principles into production cycles. The research method adopts a cognitive-physiological approach with qualitative analysis of human-machine interactions, biomechanical simulations using digital human modeling, and muscle load measurements through electromyography. Implementation was conducted using a participatory ergonomics approach and IMU sensor-based real-time monitoring systems. Results show that using materials with controlled deformation capabilities (15-20%) in work tools reduces muscle work by up to 27%, while adaptive automation system integration improves assembly accuracy by 18%. Workstations with ergonomic adjustments increase assembly speed by an average of 12%, and low-cost ergonomic interventions effectively improve productivity by 11-15% in resource-limited environments. Longitudinal analysis reveals that evidence-based ergonomic investments yield a 230% ROI through increased productivity, reduced injury compensation costs, and decreased employee turnover. IMU-based posture monitoring systems integrated with adaptive feedback loops reduced musculoskeletal disorder incidents by up to 41%. In conclusion, ergonomic optimization based on cognitive-physiological principles creates synergy between production efficiency and worker well-being, making it an essential component in achieving sustainable productivity.

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.

Posyandu is a form of Community Resource Health Effort (UKBM) which is managed from, by, for and with the community, in order to empower the community and make it easier for the community to obtain basic health services. Improving the quality of health services can be seen from the ease of obtaining services, speed and accuracy of services and affordable costs. To fulfill the provision of good services is determined by the abilities, attitudes and behavior of service officers in their interactions with the community as service recipients. The implementation of the Posyandu program did not run smoothly due to a lack of participation from the community using the service. Adequate service facilities and facilities do not necessarily make residents active in going to Posyandu. Only a small portion of the healthy behavior of mothers and children in the community are willing to implement it and obtain it through Posyandu, so the role of cadres is very influential in increasing community participation through a pick-up system and going directly into the community

Posyandu is a form of Community Resource Health Effort (UKBM) which is managed from, by, for and with the community, in order to empower the community and make it easier for the community to obtain basic health services. Improving the quality of health services can be seen from the ease of obtaining services, speed and accuracy of services and affordable costs. To fulfill the provision of good services is determined by the abilities, attitudes and behavior of service officers in their interactions with the community as service recipients. The implementation of the Posyandu program did not run smoothly due to a lack of participation from the community using the service. Adequate service facilities and facilities do not necessarily make residents active in going to Posyandu. Only a small portion of the healthy behavior of mothers and children in the community are willing to implement it and obtain it through Posyandu, so the role of cadres is very influential in increasing community participation through a pick-up system and going directly into the community

The success of stroke treatment is determined by the speed and accuracy of treatment. The golden time in treating stroke is ± 3 hours. Integrated Referral System SISRUTE is a tool that facilitates the transfer of health services between various health facilities.Rapid reporting through the web application is facilitated by this system.. The aim of this research is the relationship between the use of an integrated referral system (SISRUTE) and the speed of success in emergency treatment of stroke cases in the0AGD0of the0DKI0Jakarta0Health Office. The research method that will be used is an analytical research design with a correlational The design was cross-sectional, with a population of 340 participants and 77 participants chosen for the sample size. Using the parametric Chi-Square test. The results show a relationship between using the integrated road system (SISRUTE)..and the success rate of speed of emergency treatment of stroke cases in the0AGD0of the0DKI0Jakarta Health0Office0with a p-vlue of 0.014 < 0.05. Conclusion: The use of an integrated referral system can influence the success rate of stroke emergency treatment.