The education information delivery system at the MA Alwutsqo school is still being carried out as usual even though the pandemic outbreak in Indonesia is still not over. Because the school does not have a system to support distance learning. By implementing health protocols and teaching and learning time events, students often do not get an understanding of the material presented by the teacher. Learning Management System (LMS) is one of the systems needed by the school. Therefore, the authors designed a website-based E-learning application system with the aim of helping the learning and teaching process at MA Alwutsqo Depok City. The design of this information system uses waterfalls and system development is carried out using the Agile method. The result is that students can download the material that has been delivered and can do the exercises given by the teacher without recommendations by time and space.Keywords:E-learning, Webite, Metode Waterfall, Metode Agile, Learning Management System (LMS).
The purpose of this study was to determine the effect of leadership style, managerial ability, self-efficacy, and learning achievement on work readiness of students of the Faculty of Education, State University of Malang. This study uses a quantitative approach. The design or design of this study is an ex-post-facto cross-sectional survey and is included in the descriptive-causality research type. The population of this research is all of the management of Ormawa Faculty of Education, State University of Malang. Based on the calculation of Krejcie and Morgan Table (1970), the total population was 269 students, taken as a sample of 158 students. The instrument used in this study was a questionnaire. Analysis of the data that will be used in this study are: (1) descriptive analysis; (2) regression analysis; and (3) path analysis. Based on the results of data analysis, this study concludes: (1) there is a significant influence of leadership style (X1) on students' work readiness (Y); (2) there is a significant influence of managerial ability (X2) on student work readiness of Ormawa (Y); (3) there is a significant effect of self-efficacy (X3) on student work readiness of Ormawa (Y); (4) there is a significant effect of learning achievement (X4) on student work readiness of Ormawa (Y); and (5) there is a significant influence of leadership style (X1), managerial ability (X2), selfefficacy (X3), and learning achievement (X4) on students' work readiness (Y).
The instrument has a crucial function in a research. The accuracy of the data taken is also influenced by the validity of the research instrument. The validity of the research instrument will also affect the accuracy of research conclusions. Therefore, before using an instrument to retrieve data, its validity and reliability must be tested. This study tested the validity and reliability of the questionnaire instrument of the student leadership style variables. The indicators used to compile the questionnaire statement items for the student leadership style variables based on the theory of Yukl (2015), Usman (2013), and Gunawan (2018), namely: autocratic; bureaucratic; diplomatic; participative; and free rein leader. Based on this theory, 10 items were developed to measure the student leadership style variables. The research sample was 35 students of UKM KSR PMI Unit Universitas Negeri Malang (student organizations engaged in the red cross). The formula used to test the validity is the Pearson Product Moment Correlation formula, while the formula used to test the reliability is the Cronbach's Alpha formula. The results of the validity analysis concluded that all statement items developed (10 items) had a probability value (α) < 0.05; so it can be concluded that the instrument is valid for measuring the variable student leadership style. The results of the reliability analysis showed that the value of r alpha = 0.799 > r table = 0.468; so it can be concluded that the instrument is reliable for measuring the variable student leadership style.
Pleural effusion is a respiratory infection characterized by a buildup of fluid between the two layers of pleura, which causes specific symptoms such as chest pain and shortness of breath. In Indonesia, pleural effusion cases alone account for 2.7% of other respiratory infections, with an estimated number of sufferers in general at more than 3000 people per 1 million population annually. Pleural effusion is a severe case and can cause death if not treated immediately. Based on a study, as many as 15% of 104 patients diagnosed with pleural effusion died within 30 days. In this paper, we present a model that can detect pleural effusion based on chest x-ray images automatically using a Machine Learning algorithm. The machine learning algorithm used is Convolutional Neural Network (CNN), with the dataset used from ChestX-ray14. The number of data used was 2500 in the form of x-ray images, based on two different classes, x-ray with pleural effusion and x-ray with normal condition. The evaluation result shows that the CNN model can classify data with an accuracy of 95% of the test set data; thus, we hope it can be an alternative to assist medical diagnosis in pleural effusion detection.
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