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Misconceptions are understandings that do not conform to scientifically accepted concepts, but are believed to be true by students. Misconceptions in elementary school students tend to be resistant and difficult to change if not identified early. This study aims to analyze the misconceptions of sixth grade elementary school students on the material of the human movement system. This material is often considered complex because it involves the relationship between bones, joints, muscles, and the health of the movement system. The type of research used is quantitative with a survey design. The research subjects consisted of 19 sixth grade students of SD Negeri Growong Kidul 02 who were selected through a total sampling technique. The research instrument was 10 diagnostic test items in a four-tier format (four levels) which included the level of answer, answer confidence, reasons, and reason confidence. The results showed that students' conceptual understanding was divided into three main categories: Concept Understanding (PK) of 48.42%, Misconception (M) of 50.53%, and Lack of Understanding (KP) of 1.05%. These findings indicate that misconceptions outweigh students' conceptual understanding, particularly regarding the mechanisms of antagonistic and synergistic muscles, the function and types of joints, and the relationship between nutrition and bone health. The use of a four-tier diagnostic test proved effective in accurately distinguishing students with a true understanding from those with misconceptions. This study concludes the need for innovative learning strategies and the use of concrete media to minimize misconceptions so that students have a strong foundation of scientific knowledge for the next level of education.

Postoperative pain is a common clinical condition experienced by patients after surgical procedures and may hinder the recovery process if not properly managed. In addition to pharmacological therapy, safe and effective non-pharmacological interventions are needed, one of which is early mobilization. This study aimed to analyze the effect of early mobilization on pain reduction in postoperative surgical patients. A scoping review method was conducted based on the Arksey and O’Malley framework. Literature searches were performed using ScienceDirect, PubMed, and Google Scholar databases with a PICO strategy, including articles published within the last five years. From a total of 167,948 identified articles, 10 studies met the inclusion criteria and were included in the analysis. The results showed that early mobilization performed gradually and according to patients’ clinical conditions had a significant effect on reducing postoperative pain intensity. In addition, early mobilization was associated with improved comfort, enhanced functional recovery, and faster postoperative rehabilitation without increasing the risk of complications. Although variations were found in the timing and type of mobilization across studies, overall evidence supports that early mobilization is safe and effective. In conclusion, early mobilization can be recommended as an evidence-based nursing intervention for postoperative pain management.

Chronic liver disease is a significant health problem and places a significant burden on healthcare services. Deaths from complications of chronic liver disease (cirrhosis and cancer) account for approximately 3.5% of all deaths worldwide each year. Hepatocellular carcinoma (HCC) is a primary liver tumor, accounting for 90% of all liver tumors. Due to limitations in liver transplantation, liver resection is considered the treatment of choice for HCC patients with a single tumor and sufficient liver function reserve. Liver resection and transplantation are the only curative treatment options available for HCC patients. Surgical procedures require anesthesia. General anesthesia is the preferred method for liver tumor resection. There are five main classes of anesthetic agents: intravenous (IV) anesthetics, inhalational anesthetics, IV sedatives, synthetic opioids, and neuromuscular blocking agents. Estimated health risks depend on the extent or severity of liver disease, the nature and timing of surgery, the type of anesthesia, and other comorbidities.

The Criminal Procedure Code (KUHAP) regulates three types of decisions that may be rendered by judges in criminal proceedings. A legal issue arises in situations where a defendant is proven guilty lawfully and convincingly, yet the imposition of a criminal punishment would create a conflict between legal certainty and legal justice. Article 54 paragraph (2) of Law Number 1 of 2023 concerning the Criminal Code (KUHP) introduces a new principle known as Rechtelijk Pardon, or what is referred to as a judicial pardon ruling. This provision offers guidelines for sentencing by considering various factors related to justice and humanity. Following the reform of the Criminal Code through the inclusion of this provision, there emerges a need to reform the Criminal Procedure Code as well, specifically by incorporating the judicial pardon decision into Article 191 of KUHAP. This research employs a normative legal research method using primary and secondary data sources. The research approach utilizes statutory and conceptual approaches. The results of the study emphasize the importance of adding the judicial pardon decision to Article 191 of KUHAP so that the reform of criminal law in Indonesia maintains coherence between substantive and procedural legal reforms, thereby creating a criminal justice system that is more just, humane, and responsive to societal needs.

Motorcycles are one of the main modes of transportation widely used by the Indonesian people due to their practicality, efficiency, and ability to support daily mobility. However, many motorcycle users complain about the suboptimal engine power, especially when the vehicle is used on extreme terrains outside urban areas, such as uphill roads, rocky paths, or long distances. This situation has driven the development of various innovations in the automotive field to improve engine performance. One widely applied method is the oversize technique on the piston and piston block, which aims to increase the combustion chamber capacity, thereby maximizing the power output. This study aims to analyze the significant comparison of engine performance after the application of the oversize method on the KVY engine type, as well as to examine the factors influencing the optimization of engine performance based on the philosophy and needs of the vehicle owner. The testing method used a dynamometer to measure the increase in torque and engine power. The test results showed that the daily oversize application resulted in a torque increase of 1.19 Nm and a power increase of 0.85 Hp compared to the standard condition. Meanwhile, the oversize for competition needs showed more significant improvements, with a torque increase of 7.97 Nm and a power increase of 8.12 Hp. These findings demonstrate that the oversize method can significantly enhance engine performance according to its intended use.

This community service program aims to enhance the understanding and awareness of Micro, Small, and Medium Enterprises (MSMEs) regarding the importance of Intellectual Property Rights (IPR) certification as a form of legal protection and a means to improve business competitiveness. The activity was conducted in RW 04, Pondok Rajeg Village, Cibinong District, Bogor Regency, targeting local MSME actors. The program employed a Community Based Research (CBR) approach, emphasizing active community participation through problem analysis, target assessment, program development, and implementation stages. The main activity consisted of counseling sessions covering the concept of IPR, types of IPR, benefits of ownership, and online registration procedures through the Directorate General of Intellectual Property (DGIP). Evaluation was carried out using pre- and post-activity questionnaires. The results indicate that although all participants recognized the importance of IPR protection, their initial level of understanding was relatively low. Following the counseling session, there was a significant improvement in participants’ knowledge of IPR types and registration procedures. This program is expected to encourage MSMEs to register their intellectual property to protect innovation and enhance sustainable business competitiveness.

Papaya fruit (Carica papaya L.) is a tropical plant widely consumed as food and known to contain various bioactive metabolites with potential health benefits. The increasing interest in natural products as functional resources highlights the importance of reviewing the chemical characterization and health applications of papaya bioactive compounds. This article aims to systematically review the types of bioactive metabolites found in papaya fruit, the chemical characterization methods applied, and their potential applications in the health sector. This review was conducted through a literature study of relevant scientific articles, focusing on metabolite identification and biological activity evaluation. The results indicate that papaya fruit contains diverse bioactive metabolites, including flavonoids, phenolic compounds, alkaloids, saponins, terpenoids, and proteolytic enzymes. These compounds are commonly characterized using chromatographic and spectroscopic techniques. Several studies have reported that papaya bioactive metabolites exhibit biological activities such as antioxidant, antimicrobial, anti-inflammatory, and antidiabetic effects. This review suggests that papaya fruit has promising potential as a functional natural resource for health and pharmaceutical applications.

Aceh Tamiang Regency is an area with a high risk of annual flooding. This emergency condition often triggers a surge in environment-related diseases such as skin diseases, respiratory infections, and diarrhea. The success of managing health crises heavily depends on pharmaceutical logistics management, especially the availability of essential medicines and ease of access for refugees at evacuation points. This study aims to analyze the extent of medicine availability at community health centers and health posts, as well as to evaluate the barriers to medicine accessibility for flood victims in Aceh Tamiang Regency. This study uses a qualitative/quantitative descriptive method (choose one) with a case study approach. Primary data were collected through in-depth interviews with pharmaceutical logistics officers and surveys of flood survivors. Secondary data were obtained from the drug stock reports of the Aceh Tamiang District Health Office. Analysis was conducted on variables such as drug types, stock amounts (Buffer Stock), and distribution channels during the emergency response period. The results of the study indicate that the availability of drugs in the initial disaster phase tends to be (state the prediction, e.g., sufficient/limited). However, accessibility is often hindered by damaged road infrastructure and uneven distribution to remote posts. There is an urgent need to strengthen the logistics early warning system so that the types of medicines available match the disease patterns that emerge after floods. Although medicine stocks are generally available in central pharmacy warehouses, geographical constraints and distribution coordination are the main factors hindering accessibility. It is recommended that local governments map out alternative distribution routes and provide disaster-specific buffer stock of medicines at the sub-district level.

This study aims to design, implement, and test a prototype that automates three functions, namely watering, fertilizing, and pest control based on Arduino Uno with the ability to directly monitor soil moisture and pH. This system is equipped with four main types of sensors. Soil condition monitoring involves an FC-28 soil moisture sensor and a soil pH sensor, water level measurement involves an HC-SR04 ultrasonic sensor, and pest detection in the plant area involves a RIP sensor. All data obtained from these sensors is then processed by the Arduino Uno microcontroller to automatically activate actuators such as water pumps, liquid fertilizer pumps, buzzers, and DC motors according to soil conditions and plant needs. Prototype testing was conducted on simulated land with various scenarios of moisture, soil pH, and pest activity. The test results revealed that the system was proven to be able to significantly optimize water and fertilizer utilization, as well as reduce pest disturbances that could potentially damage plants.  In addition, this system also displays the operational status directly through an LCD screen, making it easy for users to monitor. The advantage of this system is its multi-function integration in a single device that is cost-effective and easy to operate. In the future, the functionality of this system can be improved through integration with Internet of Things (IoT) technology, enabling remote monitoring and control with greater efficiency. More broadly, this study is expected to support increased production and sustainable agricultural practices in Indonesia.

Financial literacy is a crucial competency for today’s young generation, especially Gen Z, who are currently in the midst of the development of financial technology. However, the level of financial literacy among vocational and high school students is still relatively low, including students at SMK Negeri 1 Musuk. This community service activity, which includes outreach activities, aims to provide and improve students’ understanding and also change students’ attitudes towards financial literacy so they can manage their finances well, wisely, and responsibly. The method used in this outreach activity is a qualitative method with a type of outreach activity consisting of several stages or sessions: the first is the observation session, the second is the activity planning, and the third is the implementation of the outreach activity. This activity was carried out on December 5, 2025, with 30 participants from class XI AKL 1 participating in this activity. The material presented consisted of the definition of financial literacy, factors, impacts, financial management strategies, as well as case studies or real examples of financial literacy. The results of this activity indicate that there is an increase in students’ understanding in learning financial literacy material, marked by students’ enthusiasm to listen and focus on the material presented. Not to mention, there were quite positive results from this activity: the students became more active in learning, as evidenced by the way they answered the questions I posed. This activity had a very positive impact on the younger generation, fostering awareness of the importance of financial literacy for their future.

Contemporary digital advancements have significantly impacted the manner in which individuals engage in economic activities, as evidenced by the rising volume of online transactions. While offering convenience and efficiency, electronic transactions also provide numerous legal challenges, especially regarding seller defaults, including delayed delivery, goods that do not conform to the agreement, or sellers failing to meet their duties post-payment by consumers. This scenario may result in consumer losses, necessitating sufficient legal certainty and protection. This study seeks to analyze the legal regulations pertaining to contracts and defaults in digital platform transactions and to evaluate the types of legal liabilities that may be placed on sellers. This study employs normative legal research, focusing on legislative and conceptual approaches, and utilizes primary, secondary, and tertiary legal materials as data references. The study's findings reveal that seller liability regulations in electronic transactions are defined in the Civil Code, the Consumer Protection Law, and the Law on Electronic Information and Transactions. Nonetheless, its execution has several challenges, especially concerning evidence and the efficacy of law enforcement measures. Consequently, it is imperative to enhance the function of marketplaces and establish more adaptive legislative frameworks to guarantee consumer protection and restitution for losses in online commerce.  

Indonesian language learning in elementary schools, especially on figurative language, still faces various problems, such as difficult to understand material, limited learning media, and low student interest and understanding. This is also experienced by fifth-grade students of SD 1 Mlati Lor who have difficulty recognizing types of figurative language and understanding their meaning well in context. This study aims to develop an interactive flipbook media about figurative language that highlights the local wisdom of North Sulawesi and test its feasibility and practicality for semantic learning. The method used in this study is research and development (R&D) with the ADDIE model, which consists of analysis, design, development, implementation, and evaluation. The research subjects were fifth-grade students of SD Negeri 1 Mlati Lor. Data collection was carried out through interviews, observations, validation by material and media experts, questionnaires for teachers and students, and learning outcome tests. Data were analyzed using qualitative and quantitative descriptive approaches. The results of the study indicate that the interactive flipbook media inspired by the local wisdom of North Sulawesi was considered very valid by experts. Furthermore, practicality testing demonstrated that teachers and students responded in the "very practical" category, indicating that the media was easy to use and well-received in learning. The application of local cultural elements has been shown to help students understand figurative language concepts more clearly and meaningfully. Therefore, the developed flipbook can be used as an alternative Indonesian language learning medium to improve students' semantic understanding and cultural knowledge in elementary schools.

The era of digitalization demands that the world of education adapt quickly to technological developments. One of the basic skills that elementary school students need to have is the ability to operate a computer, particularly in typing and using word processing applications. Community service research was conducted at the Kemala Bhayangkari Foundation 1 Medan with the aim of improving students' digital literacy thru typing training using Microsoft Word and the interactive media 10fastfingers.com. The training method is conducted using a workshop model, which consists of two main topics. The first material is a basic introduction to typing using the ASDF;LKJ pattern and the use of important keyboard keys. The second material is an introduction to basic Microsoft Word features, such as changing font type and size, using Bold, Italic, Underline, changing text color, and highlighting. Additionally, students are trained to use 10fastfingers.com to interactively improve their typing speed and accuracy. The research instruments are pretest-posttest, observation, and student response questionnaires. The research results show a significant improvement in typing skills. Average speed increased from 8–10 words per minute to 20–25 words per minute, with over 85% accuracy. Student responses were also very positive; they felt more confident, more motivated, and able to use Microsoft Word more effectively. This training program has proven effective in improving digital literacy among elementary school students while also fostering an interest in technology-based learning.

The advancement of information technology has increased young children’s exposure to digital devices, which potentially affects language development. This study aims to analyze the relationship between daily screen time duration and language development of children aged 5–6 years in Desa Mendalo Indah, Kecamatan Jambi Luar Kota, Kabupaten Muaro Jambi. This research employed a descriptive qualitative approach with a case study design. The subjects were six children aged 5–6 years who had more than two hours of daily screen time. Data were collected through observations of children’s language abilities, interviews with parents, and documentation of daily activities, and analyzed using Miles and Huberman’s (2014) interactive model, including data reduction, data display, and conclusion drawing. The results showed variations in children’s language abilities despite having relatively similar screen time durations. Children who received active parental guidance and accessed educational content demonstrated better receptive and expressive language skills, including following sequential instructions, forming simple sentences, and expressing ideas verbally. Conversely, children who used screen time passively without supervision tended to have limitations in vocabulary acquisition, concentration, and verbal interaction. These findings indicate that screen time duration alone is not the sole determinant of children’s language development; it is also influenced by the quality of parental guidance, the type of content accessed, and social interaction experiences. This study is expected to provide guidance for parents, teachers, and early childhood education practitioners in managing digital media use wisely to optimally support children’s language development.

Concept drift, the phenomenon where the statistical properties of data streams change over time, poses a significant challenge in machine learning, particularly for long term data streams. Traditional machine learning models, including batch learning and non-adaptive approaches, struggle to detect and adapt to these changes, leading to degraded performance and inaccurate predictions. This study proposes an adaptive computational model designed to detect and respond to concept drift using incremental learning techniques and statistical drift detection mechanisms. The model integrates an Adaptive Drift Detector (ADD) and Incremental Learning System, enabling real-time adjustments to data distribution changes. The model is evaluated across synthetic and real-world datasets, demonstrating its superior ability to detect abrupt, gradual, and recurring drifts compared to traditional models. Experimental results indicate that the adaptive model maintains high prediction accuracy, minimizes false positive rates, and reduces detection delays. Furthermore, the model performs well in resource-constrained environments, making it suitable for real-time applications such as healthcare prediction, fault detection, and IoT systems. Despite its promising performance, the study identifies challenges related to computational complexity and the model’s performance with imbalanced datasets and noisy data. Future research should focus on optimizing the model’s scalability, computational efficiency, and adaptability to more complex data types to ensure broader applicability in dynamic environments. This work contributes to advancing the detection and adaptation of concept drift, offering a robust solution for dynamic and evolving data streams.

Edge-Internet of Things (Edge IoT) systems are increasingly integral to applications that require real time signal processing, particularly where low latency and energy efficiency are critical. This paper explores the design and performance evaluation of a heterogeneous microprocessor architecture aimed at optimizing energy consumption and real time performance. The heterogeneous architecture integrates multiple types of cores, such as Central Processing Units (CPUs), Digital Signal Processors (DSPs), and Graphics Processing Units (GPUs), to allocate tasks based on computational demand. The proposed design significantly reduces energy consumption, particularly during high-performance tasks, while maintaining real time processing guarantees. Simulation-based performance evaluation was conducted to assess the energy efficiency, latency, and overall system performance under varying workloads, including real time Digital Signal Processing (DSP) benchmarks. The results showed that the heterogeneous architecture outperformed traditional homogeneous processors, demonstrating up to a 19-fold improvement in energy efficiency. Furthermore, the system reduced latency by up to 45% in real time applications, making it particularly suitable for Edge IoT environments such as industrial automation and smart healthcare, where both performance and energy efficiency are critical. Despite some trade-offs in task scheduling complexity, the heterogeneous design was able to balance power consumption and computational performance effectively. The findings suggest that this architecture can serve as a foundation for future Edge IoT systems, providing significant advantages in terms of energy efficiency, real time processing, and scalability. Future work will focus on further optimization of the architecture and exploring its application across various IoT environments.

Diabetes mellitus (DM) is a global health problem characterized by increased blood glucose levels. Type 2 diabetes mellitus (T2DM) accounts for 90-95% of all diabetes cases and is characterized by insulin resistance. Persistent hyperglycemia in patients with T2DM increases the risk of various complications, including renal dysfunction. Therefore, monitoring HbA1c levels is important for assessing long-term glycemic control and preventing complications, one of which is impaired kidney function that can be detected through increased blood creatinine levels. To analyze the relationship between HbA1c levels and blood creatinine levels in type 2 diabetes mellitus patients at RSUD ODSK North Sulawesi Province. This study used an observational analytic design with a cross-sectional approach. This study was retrospective using secondary data in the form of medical record data for the period February 2024-August 2025. This study used a total sampling method with 71 patients who met the inclusion criteria. The findings showed that the majority of patients had HbA1c levels >6,5%, while most blood creatinine levels were within the normal range. Based on the results of the Spearman-Rank correlation test, a significance value of 0.040 (p-value <0.05) was obtained. There is a significant relationship between HbA1c levels and blood creatinine levels, with a negative correlation strength in patients with type 2 diabetes mellitus at RSUD ODSK North Sulawesi Province.

Explainable Artificial Intelligence (XAI) has become a critical area of research within artificial intelligence, focusing on improving the transparency and interpretability of machine learning (ML) models, often referred to as "black-box" models. The need for XAI techniques arises from the inherent complexity of ML models, which can make their decision-making processes difficult for users to understand. This study investigates various XAI techniques, including LIME (Local Interpretable Model-agnostic Explanations) and SHAP (SHapley Additive exPlanations), to assess their impact on model interpretability without significantly compromising predictive performance. A comparative experimental design was used, applying these XAI methods to different ML models, including deep neural networks and ensemble methods, within large-scale enterprise data analytics systems. The results indicate that XAI methods significantly enhance model transparency and decision traceability, allowing users to understand the influence of individual features on predictions. While a slight reduction in predictive accuracy was observed, especially with simpler models, the trade-off between interpretability and performance was deemed acceptable, particularly in fields requiring transparency, such as healthcare, finance, and autonomous systems. The use of XAI in enterprise data systems has practical implications for fostering trust and enabling informed decision-making among stakeholders. Furthermore, the study discusses the challenges and limitations of applying XAI techniques, such as complexity, scalability, and model-specific limitations. Future research is suggested to focus on developing more scalable and efficient XAI methods, enhancing their applicability across various model types, and addressing the challenges of real-time applications. This will be crucial in ensuring the widespread adoption of XAI in critical domains, promoting the ethical use of AI while maintaining predictive accuracy.

This study aims to determine the effect of price and service quality on customer satisfaction of members of the Merah Putih Candiroto Village Cooperative, Kendal District, Kendal Regency. This study uses a quantitative approach, associative research type, with a sample of members of the Merah Putih Candiroto Village Cooperative, Kendal. The sampling method was carried out using a saturated sampling technique. The total sample in this study was 137 respondents. The variables in this study were independent variables: price and service quality, and the dependent variable: customer satisfaction of members of the Merah Putih Candiroto Village Cooperative, Kendal. Testing in this study used instrument testing, classical assumption testing, and hypothesis testing with multiple regression tests using SPSS Version 25. The results of this study indicate that partially the price has a positive and significant effect on customer satisfaction of members of the Merah Putih Village Cooperative, Candiroto, Kendal with a t-count of 3.418 greater than the t-table of 0.1678 and a significant value of 0.001 smaller than the significance level of 0.05. And the quality of service partially has a positive and significant effect on customer satisfaction of members of the Merah Putih  Village Cooperative, Candiroto, Kendal with a t-count of 3.643 greater than the t-table of 0.1678 and a significant value of 0.000 smaller than the significance level of 0.05. Price and service quality simultaneously have a positive and significant effect on customer satisfaction of members of the Merah Putih Village Cooperative, Candiroto, Kendal, with F count of 715.041 greater than F table of 0.1678 with a significance of 0.000 smaller than the significance level of 0.05. The Adjusted R square result of 0.913 indicates that 91.3% of customer satisfaction of members of the Merah Putih Village Cooperative, Candiroto, Kendal, is influenced by price and service quality whose influence was tested in this study, while the remaining 8.7% is influenced by other variables not examined in this study.

In high-performance computing (HPC) environments, the need to balance memory efficiency and query performance is crucial for ensuring optimal system performance. Traditional data structures, such as B-trees and hash tables, often prioritize either memory usage or query speed, leading to suboptimal performance in memory-constrained systems. This paper proposes a hybrid data structure that combines the strengths of multiple traditional data structures to optimize both memory usage and query processing speed. The proposed hybrid structure integrates cache-conscious algorithms, dynamic memory allocation, and compression techniques for intermediate query results. The approach is evaluated through extensive benchmarking tests comparing it to standard data structures like B-trees and hash tables under various workloads. Results show that the hybrid data structure reduces memory overhead by up to 30% while maintaining query processing speeds up to 1.5 times faster than conventional methods. Furthermore, the hybrid structure demonstrates robust performance across different types of queries, including both point and range queries, ensuring versatility and efficiency. The findings indicate that this hybrid approach provides a promising solution for HPC systems, where both memory efficiency and query speed are essential. Future research can explore extending the hybrid structure to distributed systems and emerging technologies, further improving its scalability and adaptability to new computational paradigms.