bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Post-Operative Survival Expectancy in Thoracic Lung Cancer Surgery Using Extreme Learning Machine and SMOTE
Authors: Helisa Ajwa , Saragih Triando Hamonangan , Budiman Irwan , Indriani Fatma , Kartini Dwi
Published: January 2025

Lung cancer is the most common cause of cancer death globally. Thoracic surgery is a common treatment for patients with lung cancer. However, there are many risks and postoperative complications leading to death. In this study, we will predict life expectancy for lung cancer patients one year after thoracic surgery The data used is secondary data for lung cancer patients in 2007-2011. There are 470 data consisting of 70 death class data and 400 survival class data for one year after surgery. The algorithm used is Extreme learning machine (ELM) for classification, which tends to be fast in the learning process and has good generalization performance. Synthetic Minority Over-sampling (SMOTE) is used to solve the problem of imbalanced data. The proposed solution combines the benefits of using SMOTE for imbalanced data along with ELM. The results show ELM and SMOTE outperform other algorithms such as Naïve Bayes, Decision stump, J48, and Random Forest. The best results on ELM were obtained at 50 neurons with 89.1% accuracy, F-Measure 0.86, and ROC 0.794. In the combination of ELM and SMOTE, the accuracy is 85.22%, F-measure 0.864, and ROC 0.855 on neuron 45 using a data division proportion of 90:10. The test results show that the proposed method can significantly improve the performance of the ELM algorithm in overcoming class imbalance. The contribution of this study is to build a machine learning model with good performance so that it can be a support system for medical informatics experts and doctors in early detection to predict the life expectancy of lung cancer patients.
Pilates Pose Classification Using MediaPipe and Convolutional Neural Networks with Transfer Learning
Authors: Tanjaya Kenneth Angelo , Naufal Mohammad Farid , Arwoko Heru
Published: January 2025

A sedentary lifestyle can lead to heart disease, cancer, and type 2 diabetes. An anaerobic exercise called pilates can address these problems. Although pilates training can provide health benefits, the heavy load of pilates poses may cause severe muscle injury if not done properly. Surveys have found that many teenagers are unaware of the movements in pilates poses. Therefore, a system is needed to help users classify pilates poses accurately. MediaPipe is a system that accurately extracts the real time human body skeleton. Convolutional Neural Network (CNN) with transfer learning is an accurate method for image classification. There have been several studies investigated pilates poses classification. However, there is still no research applies the MediaPipe as a skeleton feature extractor and CNN with a transfer learning to classify pilates poses. In addition, previous research still does not implement the pilates poses classification in real-time. Based on this problem, this study creates a system using MediaPipe as a feature extractor and CNN with transfer learning as a real-time pilates poses classifier. This system runs on a mobile device and gets information from a camera sensor. The results from MediaPipe then be classified by pre-trained CNN architectures with transfer learning: MobileNetV2, Xception, and ResNet50. The best model was obtained by MobileNetV2, which had an f1 score of 98%. Ten people who didn't know much about Pilates also tested the system. They all agreed that the app could accurately identify Pilates poses, make people more interested in Pilates, and help them learn more about Pilates.
Implementation of Machine Learning and Deep Learning Models Based on Structural MRI for Identification Autism Spectrum Disorder
Authors: Saputra Dimas Chaerul Ekty , Maulana Yusuf , Win Thinzar Aung , Phann Raksmey , Caesarendra Wahyu
Published: January 2025

Autism spectrum disorder (ASD) is a developmental disability resulting from neurological disparities. People with ASD frequently struggle with communication and social interaction, as well as limited or repetitive interests or behaviors. People with ASD may also have unique learning, movement, and attention styles. ASD sufferers can be interpreted as 1 in every 100 individuals in the globe having ASD. Abilities and requirements of autistic individuals vary and may change over time. Some autistic individuals are able to live independently, while others have severe disabilities and require lifelong care and support. Autism frequently interferes with educational and employment opportunities. Additionally, the demands placed on families providing care and assistance can be substantial. Important determinants of the quality of life for persons with autism are the attitudes of the community and the level of support provided by local and national authorities. Autism is frequently not diagnosed until adolescence, despite the fact that autistic traits are detectable in early infancy. This study will discuss the identification of Autism Spectrum Disorders using Magnetic Resonance Imaging (MRI). MRI images of ASD patients and MRI images of patients without ASD were compared. By employing multiple machine learning and deep learning techniques, such as random forests, support vector machines, and convolutional neural networks, the random forest method achieves the utmost accuracy with 100% using confusion matrix. Therefore, this technique is able to optimally identify ASD through MRI.
Application of SMOTE to Handle Imbalance Class in Deposit Classification Using the Extreme Gradient Boosting Algorithm
Authors: Arifah Dina , Saragih Triando Hamonangan , Kartini Dwi , Muliadi Muliadi , Mazdadi Muhammad Itqan
Published: January 2025

Deposits became one of the main products and funding sources for banks and increasing deposit marketing is very important. However, telemarketing as a form of deposit marketing is less effective and efficient as it requires calling every customer for deposit offers. Therefore, the identification of potential deposit customers was necessary so that telemarketing became more effective and efficient by targeting the right customers, thus improving bank marketing performance with the ultimate goal of increasing sources of funding for banks. To identify customers, data mining is used with the UCI Bank Marketing Dataset from a Portuguese banking institution. This dataset consists of 45,211 records with 17 attributes. The classification algorithm used is Extreme Gradient Boosting (XGBoost) which is suitable for large data. The data used has a high-class imbalance, with "yes" and "no" percentages of 11.7% and 88.3%, respectively. Therefore, the proposed solution in the research, which focused on addressing the Imbalance Class in the Bank marketing dataset, was to use Synthetic Minority Over-sampling (SMOTE) and the XGBoost method. The result of the XGBoost study was an accuracy of 0.91016, precision of 0.79476, recall of 0.72928, F1-Score of 0.56198, ROC Area of 0.93831, and AUCPR of 0.63886. After SMOTE was applied, the accuracy was 0.91072, the precision was 0.78883, the recall was 0.75588, F1-Score was 0.59153, ROC Area was 0.93723, and AUCPR was 0.63733. The results showed that XGBoost and SMOTE could outperform other algorithms such as K-Nearest Neighbor, Random Forest, Logistic Regression, Artificial Neural Network, Naïve Bayes, and Support Vector Machine in terms of accuracy. This study contributes to the development of effective machine learning models that can be used as a support system for information technology experts in the finance and banking industries to identify potential customers interested in subscribing to deposits and increasing bank funding sources.
Design and Implementation of Embedded Biometric-Based Access Control System with Electronic Lock using Raspberry Pi
Authors: Elmir Youssef , Abdelaziz Abdeldjalil , Haidas Mohammed
Published: January 2025

This paper presents the design and implementation of an improved access control system based on biometric recognition, utilising Raspberry Pi technology. The proposed system aims to enhance the security of the existing electronic lock-based system at the SGRE-Lab of University Tahri Mohammed of Bechar in Algeria. The proposed system employs multimodal biometrics, integrating facial recognition and speaker verification for personal identification. Following initial verification by the electronic lock, the system captures the user's face through a camera to perform facial recognition. In cases where the user's identity is uncertain, a voice recognition module prompts the user to say a secret word, confirming their identity through the microphone. The combination of these two biometric techniques ensures access is granted, and an access log is recorded, with an accompanying notification sent to the administrator via SMS. As technical contribution, this paper presents the design and implementation of an embedded biometric-based access control system using Raspberry Pi, which includes the integration with an electronic lock and digicode, in the other hand, a second innovation contribution by combining biometric-based authentication with Raspberry Pi technology, this paper introduces an innovative approach to access control systems that provides a more secure and reliable means of access control than traditional methods based on keys or passwords. An overview of the proposed system's architecture is provided, its operation modes, and necessary hardware and software requirements. The promising obtained results of demonstrations show a notable improvement in security levels, characterized by reduction of false acceptances, however, the paper acknowledges that users unfamiliar with the biometric system may face challenges, potentially leading to false rejections. Future work should focus on mitigating these challenges and addressing user familiarity issues.
Eidos System Prediction of Myopia in Children in Early Education Stages
Authors: Al-Ansi Abdullah M. , Almadi Mudar , Ichhpujani Parul , Ryabtsev Vladimir
Published: January 2025

This study used a database containing factors that, when processed using the Eidos intellectual system, detect myopia in children of primary school age. The database includes parameters that take into account the properties of the visual system, as well as factors that determine the duration of the performance of the main functions of the cognitive and entertaining nature of the students. The results obtained allow us to determine those factors that are more conducive to the appearance of myopia. The negative impact of some factors that cause myopia can be removed, such as, limiting the screen time spent, increasing outdoor activities/sports. A retrospective training sample can be used for automated processing using the Eidos intellectual system of the results obtained during the preventive examination of schoolchildren by an ophthalmologist. Early intervention towards myopia management in students, improves the chances of maintaining vision and slows myopia progression. The contribution of this research includes factors of a social nature that could be influenced at school in the process of education, increasing the attention towards childent, awareness of maintaining vision and slows down the progression of myopia.
Aspect-Based Sentiment Analysis from User-Generated Content in Shopee Marketplace Platform
Authors: Cahyani Andharini Dwi
Published: January 2025

A number of businesses, such as TripAdvisor, Open Table, and Yelp, have successfully utilized aspect-based sentiment analysis in order to gain insights from reviews provided by customers and enhance the quality of their goods or services.  Businesses are able to swiftly discover any unfavorable sentiment or possible harm to their brand when they analyze client input across numerous aspects from social media, online reviews, and conversations with customer care representatives. This study aims to explain how aspect-based semantic analysis of market-collected user-generated data through performance comparisons of Doc2vec and TF-IDF vectorization. Both Doc2Vec and TF-IDF have their own distinctive qualities, which might vary according on the nature of the job, the dataset, and the volume of the available training data. For the objectives of this research, the data was obtained from several of fashion merchants that run their companies by means of the Shopee platform, which is a well-known online marketplace platform in Indonesia.  In this research, the accuracy and F1 Score achieved by Doc2Vec vectorization was superior to those achieved by TF-IDF vectorization. Our findings shows that Doc2Vec vectorization is better for classifying customer ratings because it can pull out the semantic meaning of words in a document. The findings also shows that the score of c and gamma parameter have significant impact to the score of Accuracy and F1 Score of the classifier.By precisely categorizing client sentiment, this study enables businesses to improve their services, respond to customers' problems, and increase their customer satisfaction.
Forecasting Solar Irradiation on Solar Tubes Using the LSTM Method and Exponential Smoothing
Authors: Handoko Wahyu Tri , Muladi Muladi , Handayani Anik Nur
Published: January 2025

Sunlight is an alternative energy source that can be used as a substitute for fossil fuels. Renewable energy potential has not been widely utilized, especially in Indonesia. Utilization of sunlight, one of which is done indoors to save electricity and the source is not limited. This study aims to predict solar irradiance to determine the value of sunlight intensity in an area as the main source of the utilization of renewable electrical energy through the solar tube system with the LSTM method. This low-cost system offers a renewable way and considers the potential for solar radiation as an energy-efficient alternative based on the intensity of light captured by the solar tube. This research uses two methods. The LSTM method is a recurrent neural network forecasting technique that can study deeply and extract temporal relationships in data because of its large architecture. The exponential smoothing method is part of the time series forecasting technique and is used when the dataset has no cyclic variance and trend. Data collection was carried out in sunny conditions because it represents a stable condition in sunlight. The results obtained from the two methods are evaluated with RMSE and MAE values to choose the optimal approach. Due to lower RMSE and MAE values in this comparison, LSTM performs better than Multiple Repeat and Exponential Smoothing in terms of performance.
Network Slicing Using FlowVisor for Enforcement of Bandwidth Isolation in SDN Virtual Networks
Authors: Monita Vivi , Wendanto Wisnu , Anggiratih Endang
Published: January 2025

Software-defined networking (SDN) is becoming increasingly popular because of features such as programming control, embedded monitoring, fine-grained control, flexibility, support for many tenants, and scalability. Problems with the prior design, known as the conventional network, include the need to configure each network device individually, decentralized control, and a persistent issue with tenant enforcement for multitenant support. Tenants are unable to administer their networks without disturbing their neighbours. In this research, network slicing on SDN will ensure tenant isolation using FlowVisor and an SDN controller. Flowspace, which is part of FlowVisor capable of implementing network isolation, is for isolation in this research. Multitenancy is supported in SDN via the network slicing technique. Two types of renters were employed, and two testing procedures connectivity and functionality were run to meet the research objectives. This research produced several findings, including that all hosts were correctly linked, and the connection was achieved without turning on FlowVisor. The host function can only send and receive data from hosts with the same tenant. The research results show that FlowVisor can be applied for isolation enforcement. As a result of each tenant utilising their slice of the network without being interrupted by other slices, this research finds that utilising FlowVisor to construct Flowspace can segment the network to allow multitenancy. Expanding the number of slices for more study and testing in a real-world setting is possible.
Design and Implementation of IoT-Based Burglary Detection System
Authors: Jassem Mokhalad Mahdi , Al-Nouman Mohammed
Published: January 2025

This paper aims to design and implement an IoT-based anti-theft security system. The system uses fingerprint recognition technology to grant access to a building only if the fingerprint matches the stored data. In case of unauthorized access attempts, the system captures a photo of the person and sends an immediate alert to the homeowner via the Telegram API. The proposed paper methodology involves analyzing existing systems, identifying research gaps, and developing a generally implementable framework. The proposed system is implemented using Raspberry Pi as the main control unit and incorporates components like the R305 Fingerprint Recognition Sensor, Camera Pi for video surveillance, and additional hardware for door control and sensor integration. Through practical testing, the implemented system demonstrates reliable burglary detection and notification capabilities, enhancing home or building security. Finally, the obtained research results offer valuable insights for future developments in anti-theft security systems.
Development of Customer Loyalty Measurement Application Using R Shiny with Structural Equation Model Partial Least Square Method, Customer Satisfaction Index, and Customer Loyalty Index
Authors: Oktavia Cintika , Warsito Budi , Kadarrisman Vincensius Gunawan Slamet
Published: January 2025

One of Indonesia's well-known e-commerce platforms, Shopee, relies on information technology to run its business. The information technology used by Shopee is considered unable to meet customer satisfaction. Customer reviews are dissatisfied with the facilities provided by Shopee, and some customers compare Shopee with other e-commerce sites. The research contribution is the understanding that the proper use of information technology can positively impact customer experience, improve operational efficiency, and support business growth in the e-commerce industry. Research with a quantitative approach will build a website-based application as a statistical tool for data processing using R shiny so that the application results have high interactivity, dynamic visualization, and better explanation. The research will collect 100 data provided to customers who have transacted at Shopee and distributed through the telegram application, which is distributed to particular groups and channels for Shopee users. Data processing for this study will use the  Structural Equation Model Partial Least Square, Customer Satisfaction Index, Net Promoter Score, and Customer Loyalty Index. The study results show that electronic service quality and security seals positively and significantly affect customer satisfaction. Electronic service quality has a moderate effect on customer satisfaction, while electronic security seals have a slightly lower effect on customer satisfaction (t=5.584, p<0.001). Additionally, a significant correlation between customer loyalty and satisfaction was discovered (t=14.764, p=0.001). Research proves the need to improve service quality and security aspects to increase customer satisfaction on e-commerce platforms and the importance of maintaining customer satisfaction as a strategy to increase customer loyalty.
Intellectual System Diagnostics Glaucoma
Authors: Ichhpujani Parul , Ryabtsev Vladimir , Utkina Tetyana Yuriyivna
Published: January 2025

Glaucoma is a chronic eye disease that can lead to permanent vision loss. However, glaucoma is a difficult disease to diagnose because there is no pattern in the distribution of nerve fibers in the ocular fundus. Spectral analysis of the ocular fundus images was performed using the Eidos intelligent system. From the ACRIMA eye image database, 90.7% of healthy eye images were recognized with an average similarity score of 0.588 and 74.42% of glaucoma eye images with an average similarity score of 0.558. The reliability of eye image recognition can be achieved by increasing the number of digitized parameters of eye images obtained, for example, by optical coherence tomography. The research contribution is the digital processing of fundus graphic images by the intelligent system “Eidos”. The scientific contribution lies in the automation of the glaucoma diagnosis process using digitized data. The results of the study can be used at medical faculties of universities to carry out automated diagnostics of glaucoma.
A Hybrid Genetic Algorithm-Random Forest Regression Method for Optimum Driver Selection in Online Food Delivery
Authors: Putrada Aji Gautama , Alamsyah Nur , Oktaviani Ikke Dian , Fauzan Mohamad Nurkamal
Published: January 2025

The online food delivery trend has become rapid due to the COVID-19 incident, which limited mobility, while the broader challenge in the online food delivery system is maximizing quality of service (QoS). However, studies show that driver selection and delivery time are important in customer satisfaction. The solution is our research aim, which is the selection of optimal drivers for online food delivery using random forest regression and the genetic algorithm (GA) method. Our research contribution is a novel approach to minimizing delivery time in online food delivery by combining a random forest regression model and genetic algorithms. We compare random forest regression with three other state-of-the-art regression models: linear regression, k-nearest neighbor (KNN), and adaptive boosting (AdaBoost) regression. We compare the four models with metrics including , mean squared error (MSE), root mean squared error (RMSE), mean total error (MAE), and mean absolute percentage error (MAPE). We use the optimum model as the fitness function in GA. The test results show that random forest performs better than linear, KNN, and AdaBoost regression, with an , RMSE, and MAE value of 0.98, 54.3, and 11, respectively. We leverage the optimum random forest regression model as the GA fitness function. The best efficiency is reducing the delivery time from 54 to 15 minutes, achieved through rigorous testing on various cases. In addition, by completing this research, we also achieve some practical implications, such as an increase in customer satisfaction, a reduction in cost, and a paramount finding in the field of data-driven decision-making. The first key finding is an optimum driver selection model in random forest regression, while the second is an optimum driver selection model in GA.
Analysis of Specific Water Consumption Based on Water Discharge Case Study of Batang Agam Hydroelectric Power Plant
Authors: Rajagukguk Antonius , Ervianto Edy , Firdaus Firdaus , Putri Anjelina Ifelia
Published: January 2025

Renewable energy has an important role today, one of which is hydroelectric power plants which use water as the main resource. So the amount of water is very important for producing every 1 kWh of electricity, this is called specific water consumption. Each hydropower plant has different SWC standards. The research was carried out to determine the SWC value and generator efficiency at the Batang Agam Hydroelectric Power Plant in the period April 2022 to April 2023. The research method was carried out by observing and collecting the required data such as inflow, outflow and daily electrical energy distribution data. Calculate water volume, hydraulic energy and specific water consumption. The research results show that the swc is in the range of 3 -4 m3/kWh, which means this value is below the standard swc value for the Batang Agam Hydroelectric Power Plant, namely 4,808 m3/kWh. This is caused by the unstable condition of the water flow flowing from the river to the Batang Agam Hydroelectric Power Plant which is influenced by rainfall. And based on the electrical energy generated with the distributed electrical energy, the efficiency of the Batang Agam Hydroelectric Power Plant for one year is 71.66%.
GLCM-Based Feature Combination for Extraction Model Optimization in Object Detection Using Machine Learning
Authors: Kurniati Florentina Tatrin , Sembiring Irwan , Setiawan Adi , Setyawan Iwan , Huizen Roy Rudolf
Published: January 2025

In the era of modern technology, object detection using the Gray Level Co-occurrence Matrix (GLCM) extraction method plays a crucial role in object recognition processes. It finds applications in real-time scenarios such as security surveillance and autonomous vehicle navigation, among others. Computational efficiency becomes a critical factor in achieving real-time object detection. Hence, there is a need for a detection model with low complexity and satisfactory accuracy. This research aims to enhance computational efficiency by selecting appropriate features within the GLCM framework. Two classification models, namely K-Nearest Neighbours (K-NN) and Support Vector Machine (SVM), were employed, with the results indicating that K-Nearest Neighbours (K-NN) outperforms SVM in terms of computational complexity. Specifically, K-NN, when utilizing a combination of Correlation, Energy, and Homogeneity features, achieves a 100% accuracy rate with low complexity. Moreover, when using a combination of Energy and Homogeneity features, K-NN attains an almost perfect accuracy level of 99.9889%, while maintaining low complexity. On the other hand, despite SVM achieving 100% accuracy in certain feature combinations, its high or very high complexity can pose challenges, particularly in real-time applications. Therefore, based on the trade-off between accuracy and complexity, the K-NN model with a combination of Correlation, Energy, and Homogeneity features emerges as a more suitable choice for real-time applications that demand high accuracy and low complexity. This research provides valuable insights for optimizing object detection in various applications requiring both high accuracy and rapid responsiveness.
Use of Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA) in Trauma Patients in French Level-1 Trauma Centers: A National Survey
Authors: Glasman Pauline , Clavier Thomas , Quintard Hervé , Charbit Jonathan
Published: January 2025

Background: The goal of the present national survey was to describe the practices and use of resuscitative endovascular balloon occlusion of the aorta (REBOA) in France in level-1 trauma centers.
Methods: Between January and December 2023, the ACUTE SFAR (Société Française d’Anesthésie et de Réanimation) committee sent a numeric survey to each French level-1 trauma center. This survey was focused on REBOA in trauma management including: use, protocol (indications, placement, aortic occlusion durations), aortic occlusion location (Zone 1/Zone 3), partial occlusion (pREBOA), device characteristics, operator, specific complications.
Results: Among the 41 French level-1 trauma centers, 18 (44%) had incorporated REBOA in their algorithm. In 2022, 78% (14/18) of these centers had experienced between 1 and 5 REBOA placements, 11% (2/18) between 6 and 10, and 6% (1/18) 10 or more placements. The frequency of REBOA procedures increased with the duration of REBOA availability at the center. A protocol for REBOA placement was present in 28% (5/18) of centers. An anesthesiologistintensivist was the operator in 50% (9/18), a surgeon in 28% (5/18), and a radiologist in 22% (4/18) of centers. The proportion of centers using REBOA in Zone 1 was 39% (7/18), and pREBOA 33% (6/18). The maximum duration of complete aortic occlusion was specified in 50% of centers for Zone 1 and 78% for Zone 3.
Conclusions: Use of REBOA is modestly spread among the French trauma centers, and in less than half of centers. Specific protocols are present. Anesthesiologist-intensivists are the operators in only half of these centers.
Bringing local perspective into peacebuilding. The case of Sierra Leone Truth and Reconciliation Commission
Authors: Jiménez-Zumalde Irene
Published: January 2025

After going through an eleven yearlong violent civil war, Sierra Leone started its peacebuilding process in 2002. This operation has been considered a successful one. In the paper, I focus on one of its instruments: the Sierra Leone Truth and Reconciliation Commission (SLTRC). This body promoted truth telling to establish accountability and to know the needs in society. The aim was to determine to which extent it incorporated the local perspective. To this end, different ways of incorporating the local perspective have been used. At the same time, I also looked at its gender approach, where both successful and shortcomings were found. I conclude that neither of the perspective was well consolidated.
Differences In Physical Development And Basic Movement Activities Between Students In The Mountains And Students In The Coastal Plains In Primary School Physical Education Learning In Ngaras District
Authors: Sukmana Fajar , Rahman Trio Deswa , Putra Yuda Gastriana , Sudrazat Adang
Published: January 2025

This study aims to analyze the differences in physical development and basic motor activity between students in mountainous areas and students in coastal plains in elementary school physical education (Penjas) learning in the Ngaras District. This research uses a quantitative method with a comparative design. The research sample consisted of 20 elementary school students, 10 students from elementary schools in mountainous areas and 10 students from elementary schools in coastal plains. The research instruments used were anthropometric tests (height, weight, chest circumference, and waist circumference), physical fitness tests (running test, push-up test, and sit-up test), and basic motor activity tests. The data were analyzed using a t-test. The results showed that there were significant differences in physical development and basic motor activity between students in mountainous areas and students in coastal plains. Students in mountainous areas had a higher average height, weight, and chest circumference than students in coastal plains. Students in mountainous areas also had higher physical fitness and basic motor activity test scores than students in coastal plains. This study concludes that there are significant differences in physical development and basic motor activity between students in mountainous areas and students in coastal plains in elementary School Physical Education (PE) learning in Ngaras District. Factors that are suspected to influence this difference are environmental factors, genetic factors, and socio-economic factors.
The Influence of the Sport Education (SE) Learning Model And The Student Team Achievement Division (STAD) Learning Model On Student Motivation In Badminton
Authors: Ibrohim Ibrohim , Muhtar Tatang , Sudrazat Adang
Published: January 2025

This research aims to determine the influence of the Sport Education (SE) learning model and the Student Team Achievement Division (STAD) learning model on student motivation in badminton. This research uses an experimental method using a quantitative approach because there is a very rational treatment of the samples in the research and uses statistical calculations in the process of collecting the data obtained by the researcher. This research uses a two-group pretest-posttest design. This instrument uses the Learning Self-Regulation Questionnaire (SRQ-L). This research used a two-group pretest-posttest design. The population used a limited population of 287 PJK STKIP NU Indramayu students and the sample used random sampling of 114 PJKR STKIP NU Indramayu students Hypothesis testing used a parallel samples test and an independent samples test. The results of the hypothesis test state that 1) there is an influence between the initial test and the final test of the SE learning model, the T value is 5.14 and the Sig value is 0.00 with α = 0.05, which means 0.00 < 0.05, so the data is declared significant, which means there is a difference in influence. results of the initial test and final test of PJKR STKIP NU Indramayu students 2) there is an influence of the STAD learning model from the initial test and final test of the STAD learning model, the T value is 2.14 and the Sig value is 0.04 with α = 0.05 which means 0.04 < 0.05, then the data is declared significant, which means that there is a difference in the influence on the learning outcomes of PJKR STKIP NU Indramayu semester students. 3) there is a difference in the influence of the SE and STAD models from the Tcount value of 2.05 and the Sig value of 0.04 with α = 0.05 which means 0.04 < 0.05, then the data is declared significant, which means there is a difference in the influence of learning outcomes using the SE learning model and learning outcomes using the STAD learning model for PJK STKIP NU Indramayu students.
Evaluation of the Volleyball Sports Achievement Development Program at STIKIP Modern Ngawi
Authors: Hardianti Siti , Ambardini Rachmah Laksmi , Nuransyari Firdaus , Hidayat Neneng
Published: January 2025

Volleyball UKM STKIP Modern Ngawi is a UKM that still needs evaluation to find out the strengths and weaknesses in the achievement coaching program and the extent to which the existing achievement coaching program has achieved the set goals. the purpose of this study was to evaluate the achievement coaching program in volleyball UKM STKIP Modern Ngawi. This research is an evaluation study using the Context, Input, Process and Product (CIPP) evaluation model. The subjects in the study were 20 people consisting of 15 athletes, 3 administrators, and 2 coaches of Volleyball UKM STIKIP Modern Ngawi. Data collection techniques in this study used observation, interviews, questionnaires, and documentation. Data analysis techniques use descriptive analysis, both quantitative and qualitative. The results of the research on the evaluation of the achievement coaching program for volleyball UKM STKIP Modern Ngawi athletes in terms of Context, the background of the coaching program stated quite well (2.75), the purpose of the coaching program stated quite well (2.46), the coaching program stated that it was good (3.63). The results of Input evaluation research on the achievement coaching program for volleyball UKM STKIP Modern Ngawi explain that funding in volleyball UKM Stikip Modern Ngawi is very good (4.05). but the problem of facilities and infrastructure is still lacking (1.47). The results of Process evaluation research on the achievement coaching program for volleyball UKM STKIP Modern Ngawi, the training and coaching program is quite good, and the implementation of monitoring and evaluation states that it is very good (4.00). The results of Product evaluation research on the achievement coaching program of the STKIP Modern Ngawi volleyball UKM based on the statements of administrators, coaches and athletes are quite good (2.14). The results of evaluation research based on the statements of administrators, coaches and athletes in the volleyball UKM STKIP Modern Ngawi in terms of Context, Input, Process and Product can be concluded quite well.
Effects Of Ultrasound And Isometric Knee Exercise On Post-Recovery Anterior Cruciate Ligament Injury To Increase Quadrisep Muscle Strength
Authors: Ismaningsih Ismaningsih , Zein Renni Hidayati , Muawanah Siti
Published: January 2025

This study aims to determine the effectiveness of the physiotherapy approach using ultrasound and isometric knee exercise in post-recovery anterior cruciate ligament injury to increase quadriceps muscle strength. More than 2,000,000 cases of anterior cruciate ligament (ACL) occur worldwide. Anterior cruciate ligament injury is the most common type of ligament injury and in this condition, the knee joint requires a period of rest and recovery. Quadrisep muscle weakness often occurs after an anterior cruciate ligament (ACL) knee injury resulting in prolonged disability and an increased risk of re-injury and osteoarthritis after surgery. Injuries are classified into direct contact, indirect contact, and non-contact, where non-contact injuries are the most common. This study used pre and post-experimental methods with a sample of 10 people, and evaluation measurements were carried out using manual muscle testing. in this treatment group using the normality test using the Shapiro-Wilk test on all pre-test and post-test variables, a value of P<0.05 was obtained, which means that the data is abnormally distributed. then the treatment group data obtained the results of the normality value test before P>0.000 which means P<0.05 and the value after the intervention P<0.008 which means P>0.05, then the hypothetical results using the paired samples t-test of this study obtained a value of P = 0.004 (P<0.05) with an average value of 2,300±.21884 which means the intervention of ultrasound and isometric knee exercise in the condition of anterior cruciate ligament injury after significant in increasing quadrisep muscle strength.
Mental Toughness Profile of Adult Badminton Athletes in the Training Phase
Authors: Maharani Gina Denisa , Komarudin Komarudin , Saputra Mochamad Yamin , Novian Geraldi
Published: January 2025

Badminton athletes often lack psychological training, so this causes several problems such as mental toughness. To overcome this problem, mental toughness is proposed as a solution. The purpose of this study was to determine the mental toughness of adult badminton athletes in the training phase. The method used in this research is a descriptive method with a quantitative approach. The research instrument used is the Mental Toughness Inventory (MTI). The samples involved in this study were 12 badminton athletes. The results of data analysis show that adult badminton athletes have good mental toughness, whereas male athletes have better mental toughness abilities than female athletes.
The Effect Of Resistance Band Exercises On Leg Muscle Power In Basketball Athletes At The Bekasi Sniper Basketball Club
Authors: Lukman Alvian Fuad , Setiawan M. Arief , Wijaya Habibi Hadi , Izzuddin Deden Akbar , Gemael Qorry Armen
Published: January 2025

This research experienced difficulties when jumping for lay-ups and jump shots, therefore the researchers wanted to provide training using resistance bands to increase leg muscle power when jumping during lay-ups and jumps. shoot this type of research uses experiments with a quantitative approach and one group pretest-posttest design. The population was 30 athletes and the sample was 24 athletes using total sampling techniques. Test the instrument using a vertical jump tool. The data analysis technique uses the normality test, homogeneity test and Wilcoxon test with SPSS IBM 21. The lowest value obtained from the pretest results was 49.00 and from the posttest results was 52.00. data pretest-posttest powerSniper Basketball athlete's limbs have a p-value (Sig.) > 0.05. data pretest-posttest powerSniper Basketball athlete's limbs sig value. p > 0.05, so the data is homogeneous. t count is 5.454 and t table (df 21) 2.069 with a significance p-value of 0.000. Because the t count is 5.454 > t table 2.069, and the significance value is 0.000 < 0.05, then this result shows that there is a significant difference. Thus the alternative hypothesis (Ha) reads―There is a significant effect of practice use of resistance bandstopowerSniper Basketball athlete's limbs. It can be concluded that there is an influence of resistance bands on leg muscle power in Bekasi Sniper Basketball Club players
Life Kinetic Training And Accuracy Of Overhead Lob Strokes Of Badminton Athletes
Authors: Pathonah Alia Nur , Komarudin Komarudin , Saputra Mochamad Yamin , Novian Geraldi
Published: January 2025

Badminton players often give less attention to psychological training, resulting in various problems such as lack of concentration. To overcome this problem, life Kinetik training is proposed as a solution. This study aims to examine the difference in the effect of life Kinetik training on the accuracy of overhead lob shots of badminton athletes. The method used in this study is a quantitative experiment using a posttest-only control group design. Researchers provide treatment in the form of kinetic life training. The instrument used can smash accuracy. The research sample consisted of 10 athletes, 5 male and 5 female. Data analysis was carried out using the Independent Samples Test. The results showed that there was a significant effect of life Kinetik training on the accuracy of overhead lob shots for badminton athletes. Thus, it can be concluded that life Kinetik training is one method that can be used to improve technical skills in badminton, especially overhead lob shots
Implementation Of The Independent Curriculum On Physical Education Learning At Junior High School
Authors: Utami Hesti Nur , Azhar Novial , Fatah Tata Abdul , Rahayu Ega Trisna
Published: January 2025

Learning is an activity carried out in two directions to achieve learning goals efficiently and effectively. Implementation of the Independent Learning Curriculum in PJOK subjects at SMPIT Abdan Syakuro Lampu Iman has implemented the Independent Learning Curriculum in stages and has implemented Project Based Learning which is one of the learning activities in the Independent Learning Curriculum. The obstacle in implementing the Independent Learning Curriculum in PJOK subjects at SMPIT Abdan Syakuro Lampu Iman is that teachers still find it difficult to instil the 6 Pancasila Student Profile characters in students with the various characteristics that each student has. Apart from that, from the observations made by researchers, it is also clear that teachers have not been able to get out of their comfort zone in teaching as it can be seen that in teaching they are still comfortable with using the same methods and there is still a lack of teacher ability in using learning media, this can be seen when teachers teach Most just explain the material and then give assignments to students. The solution used in implementing the Merdeka Belajar Curriculum in PJOK subjects at SMPIT Abdan Syakuro Lampu Iman is that teachers look for information or references about learning assessments and regularly participate in training on the implementation of the Merdeka Belajar Curriculum which is held.
The Influence of Physical Condition, Skill, and Mental Factors on The ability to Play Football
Authors: Utama Chairul Arif , Maksum Ali , Kristiyandaru Advendi
Published: January 2025

This study aims to determine the contribution of physical condition, skills and mental factors to the ability to play football by players of the Mitra Surabaya Football School in the age category of 15 years in the 2024 period. In this study, quantitative descriptive is used with a correlational approach. Data collection was carried out based on all variables, including 1) physical condition (strength, movement speed, explosiveness, agility and endurance), 2) skill (passing & stopping), 3) mental (pre-match preparation mental assessment questionnaire), and 4) game performance assessment instrument (GPAI). Using descriptive statistical techniques, linearity tests, and multiple regression analysis. Based on the results of the data that have been obtained and processed through statistical procedures, the results are explained that simultaneously the factors of physical condition, skill, and mental have a significant effect on the ability to play football with a significant value of 0.017 to a value of 31.9%. Meanwhile, partially, the physical condition factor had an effect with a significance value of 0.030 with a magnitude of 0.383, the skill factor had a significant effect with a value of 0.041 at a magnitude of -0.355 which meant an inverse relationship, and the mental factor did not have a significant influence with a value of 0.164 at a magnitude of -0.236. It can be concluded that simultaneously all factors affect the ability to play, and mentally becomes a support when the capacity, physical condition and skill of the player are qualified considering that all factors affect simultaneously.
Measurement of Athletic Physical Activity In 100-meter Sprint Running Numbers In Students
Authors: Syaharani Luthfiyah , Hartati Hartati , Aryanti Silvi
Published: January 2025

This study aims to determine the results of measuring athletic physical activity in the 100-meter running number. This type of research is descriptive, using a quantitative approach and using percentage data analysis. The sample used was all students of class VII, totaling 70 students. The instrument in this study used a test that measures physical activity in the 100-meter run by measuring speed (100-meter run), endurance (1000-meter/800-meter run), strength (sit ups and push ups), and flexibility (sit and reaches). Data analysis techniques were processed by using normality and percentage tests using computer assistance (excel) and the SPSS 22 program. Based on the analysis of the percentage of data obtained from the results of physical activity running the 100-meter run, this is in a good category with a result of 60.2%. By getting each result that is for speed 70%, endurance 41%, strength 80%, and flexibility 50% the average yield is 60.2% in the good category. The results of this study imply that even if the results of measuring physical activity in the 100-meter run are good, then the results of the speed in the 100-meter run will be good and can support the daily activities carried out by students.
Relationship Between Body Mass Index And Physical Fitness Level (VO2 Max) In The Family Empowerment And Welfare Driving Team Of Pasir Gaok Village, Bogor Regency
Authors: Ta'gan Muh Amrul , Mighra Bazzar Ari , Widyaningsih Heni
Published: January 2025

This research aimed to determine the relationship between Body Mass Index and Physical Fitness Level (VO2Max) in the Family Welfare Empowerment Team (TP-PKK) in Pasir Gaok Village, Bogor Regency. This research uses quantitative descriptive research. The approach in this research uses a survey method with correlation techniques. The physical fitness measurement test uses the Rockport test method to determine the level of physical fitness (VO2 max). The population in this research was the Family Empowerment and Prosperity Mobilization Team (TP-PKK) in Pasir Gaok Village, Bogor Regency, totaling 20 people. The sampling technique is purposive sampling with the following samples: 1. Active members (TPPKK) of Pasir Gaok Village, Bogor Regency, 2. No injuries, 3. Age 20 years and over, 4. Healthy. The data taken are age, height, weight, blood pressure, and VO2 Max. The analysis uses descriptive analysis techniques. The results of the research show that there is a relationship between body mass index and physical fitness level (VO2Max), the results of measuring body mass index are in the normal category of as many as 17 members or 85%, while for the results of physical fitness level (VO2 Max), there are still many who get the sufficient category as many as 14 members or 70%. Based on the results of research analysis data on the relationship between body mass index and physical fitness level (VO2Max) in the Family Empowerment and Welfare Mobilization Team (TP-PKK) in Pasir Gaok Village, Bogor Regency, it was found to be (-0,295). This shows that the relationship between body mass index and physical fitness level (VO2Max) in the Family Empowerment and Welfare Team (TP-PKK) in Pasir Gaok Village, Bogor Regency is in the weak category.