Satya Wacana Christian University

Penelitian ini bertujuan untuk mengidentifikasi implementasi pembelajaran daring dirumah pada siswa Sekolah Dasar akibat dari adanya pandemik COVID-19. Penelitian menggunakan penelitian kepustakaan dimana dalam mengumpulkan informasi data dengan teknik dokumentasi yaitu mencari data mengenai hal-hal yang relevan dari berbagai macam yang ada di perpustakaan seperti dokumen, buku, majalah, berita. Kriteria artikel dan berita yang dipilih yaitu adanya pembahasan tentang Dampak COVID-19 dan Pembelajaran Daring di Sekolah Dasar. Dari 10 Sumber yang didapatkan, kemudian dipilih yang paling relevan dan diperoleh 3 artikel dan 6 Berita yang dipilih. Hasil dalam penelitian, menunjukkan bahwa dampak covid terhadap implementasi pembelajaran daring di Sekolah Dasar dapat terlaksanakan dengan cukup baik. Hal ini dapat dilihat dari hasil data 3 artikel dan 6 Berita yang menunjukan bahwa dampak COVID-19 terhadap implementasi pembelajaran daring di SD dapat terlaksana dengan cukup baik apabila adanya kerjasama antara guru, siswa dan orang tua dalam belajar dirumah

Abstract Feature selection becomes prominent, especially in the data sets with many variables and features. It will eliminate unimportant variables and improve the accuracy as well as the performance of classification. Random Forest has emerged as a quite useful algorithm that can handle the feature selection issue even with a higher number of variables. In this paper, we use three popular datasets with a higher number of variables (Bank Marketing, Car Evaluation Database, Human Activity Recognition Using Smartphones) to conduct the experiment. There are four main reasons why feature selection is essential. First, to simplify the model by reducing the number of parameters, next to decrease the training time, to reduce overfilling by enhancing generalization, and to avoid the curse of dimensionality. Besides, we evaluate and compare each accuracy and performance of the classification model, such as Random Forest (RF), Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and Linear Discriminant Analysis (LDA). The highest accuracy of the model is the best classifier. Practically, this paper adopts Random Forest to select the important feature in classification. Our experiments clearly show the comparative study of the RF algorithm from different perspectives. Furthermore, we compare the result of the dataset with and without essential features selection by RF methods varImp(), Boruta, and Recursive Feature Elimination (RFE) to get the best percentage accuracy and kappa. Experimental results demonstrate that Random Forest achieves a better performance in all experiment groups.

Penelitian ini bertujuan untuk mengetahui produk yang dikembangkan efektif untuk digunakan dalam pembelajaran literasi membaca. Penelitian ini menggunakan jenis penelitian dan pengembangan (R&D), dengan prosedur pengembangan oleh Sukamadinata yang dikonversi dan dimodifikasi dengan model pengembangan 4D atau Four D Models (Define, Design, Development, dan Dissminate). Pada penelitian ini peneliti hanya sampai pada prosedur pengembangan dan tidak melakukan uji coba secara langsung (Dissminate) dikarenakan kondisi darurat kesahatan akibat dampak dari covid-19. Teknik pengumpulan data yang dilakukan peneliti yaitu melalui uji pakar. Uji pakar yang digunakan adalah uji pakar materi dan uji pakar media. Data hasil validasi produk oleh pakar materi dan pakar media, akan dianalisis menggunakan teknik deskriptif presentase dan kategori untuk menunjukkan keefektivan/kelayakan media. Hasil pengembangan produk yang dilakukan peneliti melalui validasi ahli materi memperoleh skor 49 dengan presentase 81% sehingga dikategorikan sangat tinggi dan layak digunakan. Hasil validasi ahli media 1 memperoleh skor 47 dengan presentase 67%, dan hasil validasi media 2 memperoleh skor 43 dengan presentase 61% sehingga dikategorikan tinggi dan layak untuk digunakan.

BACKGROUND: For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions. METHODS: The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010-23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution. FINDINGS: Total numbers of global DALYs grew 6·1% (95% UI 4·0-8·1), from 2·64 billion (2·46-2·86) in 2010 to 2·80 billion (2·57-3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0-14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31-1·61) global DALYs in 2010, increasing to 1·80 billion (1·63-2·03) in 2023, alongside a concurrent 4·1% (1·9-6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176-209] DALYs), stroke (157 million [141-172]), and diabetes (90·2 million [75·2-107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0-107·5]), depressive disorders (26·3% [11·6-42·9]), and diabetes (14·9% [7·5-25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837-917) in 2010 to 681 million (642-736) in 2023, and a 25·8% (22·6-28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7-61·0) for diarrhoeal diseases, 42·9% (38·0-48·0) for HIV/AIDS, and 42·2% (23·6-56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6-22·0) and 24·8% (7·4-36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7-19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18-1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation-with high SBP accounting for 8·4% (6·9-10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories-behavioural, metabolic, and environmental and occupational-risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8-37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0-11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023-eg, declining by 54·4% (38·7-65·3) for unsafe sanitation, 50·5% (33·3-63·1) for unsafe water source, and 45·2% (25·6-72·0) for no access to handwashing facility, and by 44·9% (37·3-53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [-2·7 to 15·6]; non-significant). INTERPRETATION: Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors-eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG-including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic-the complex interaction of multiple health risks, social determinants, and systemic challenges-will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity. FUNDING: Gates Foundation and Bloomberg Philanthropies.

BACKGROUND: Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations. METHODS: GBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 250-draw distribution for each metric. Findings are reported as counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2023 include a correction for the misclassification of deaths due to COVID-19, updates to the method used to estimate COVID-19, and updates to the CODEm modelling framework. This analysis used 55 761 data sources, including vital registration and verbal autopsy data as well as data from surveys, censuses, surveillance systems, and cancer registries, among others. For GBD 2023, there were 312 new country-years of vital registration cause-of-death data, 3 country-years of surveillance data, 51 country-years of verbal autopsy data, and 144 country-years of other data types that were added to those used in previous GBD rounds. FINDINGS: The initial years of the COVID-19 pandemic caused shifts in long-standing rankings of the leading causes of global deaths: it ranked as the number one age-standardised cause of death at Level 3 of the GBD cause classification hierarchy in 2021. By 2023, COVID-19 dropped to the 20th place among the leading global causes, returning the rankings of the leading two causes to those typical across the time series (ie, ischaemic heart disease and stroke). While ischaemic heart disease and stroke persist as leading causes of death, there has been progress in reducing their age-standardised mortality rates globally. Four other leading causes have also shown large declines in global age-standardised mortality rates across the study period: diarrhoeal diseases, tuberculosis, stomach cancer, and measles. Other causes of death showed disparate patterns between sexes, notably for deaths from conflict and terrorism in some locations. A large reduction in age-standardised rates of YLLs occurred for neonatal disorders. Despite this, neonatal disorders remained the leading cause of global YLLs over the period studied, except in 2021, when COVID-19 was temporarily the leading cause. Compared to 1990, there has been a considerable reduction in total YLLs in many vaccine-preventable diseases, most notably diphtheria, pertussis, tetanus, and measles. In addition, this study quantified the mean age at death for all-cause mortality and cause-specific mortality and found noticeable variation by sex and location. The global all-cause mean age at death increased from 46·8 years (95% UI 46·6-47·0) in 1990 to 63·4 years (63·1-63·7) in 2023. For males, mean age increased from 45·4 years (45·1-45·7) to 61·2 years (60·7-61·6), and for females it increased from 48·5 years (48·1-48·8) to 65·9 years (65·5-66·3), from 1990 to 2023. The highest all-cause mean age at death in 2023 was found in the high-income super-region, where the mean age for females reached 80·9 years (80·9-81·0) and for males 74·8 years (74·8-74·9). By comparison, the lowest all-cause mean age at death occurred in sub-Saharan Africa, where it was 38·0 years (37·5-38·4) for females and 35·6 years (35·2-35·9) for males in 2023. Lastly, our study found that all-cause 70q0 decreased across each GBD super-region and region from 2000 to 2023, although with large variability between them. For females, we found that 70q0 notably increased from drug use disorders and conflict and terrorism. Leading causes that increased 70q0 for males also included drug use disorders, as well as diabetes. In sub-Saharan Africa, there was an increase in 70q0 for many non-communicable diseases (NCDs). Additionally, the mean age at death from NCDs was lower than the expected mean age at death for this super-region. By comparison, there was an increase in 70q0 for drug use disorders in the high-income super-region, which also had an observed mean age at death lower than the expected value. INTERPRETATION: We examined global mortality patterns over the past three decades, highlighting-with enhanced estimation methods-the impacts of major events such as the COVID-19 pandemic, in addition to broader trends such as increasing NCDs in low-income regions that reflect ongoing shifts in the global epidemiological transition. This study also delves into premature mortality patterns, exploring the interplay between age and causes of death and deepening our understanding of where targeted resources could be applied to further reduce preventable sources of mortality. We provide essential insights into global and regional health disparities, identifying locations in need of targeted interventions to address both communicable and non-communicable diseases. There is an ever-present need for strengthened health-care systems that are resilient to future pandemics and the shifting burden of disease, particularly among ageing populations in regions with high mortality rates. Robust estimates of causes of death are increasingly essential to inform health priorities and guide efforts toward achieving global health equity. The need for global collaboration to reduce preventable mortality is more important than ever, as shifting burdens of disease are affecting all nations, albeit at different paces and scales. FUNDING: Gates Foundation.

Convolutional Neural Networks (CNN) achieves perfection in traffic sign identification with enough annotated training data. The dataset determines the quality of the complete visual system based on CNN. Unfortunately, databases for traffic signs from the majority of the world's nations are few. In this scenario, Generative Adversarial Networks (GAN) may be employed to produce more realistic and varied training pictures to supplement the actual arrangement of images. The purpose of this research is to describe how the quality of synthetic pictures created by DCGAN, LSGAN, and WGAN is determined. Our work combines synthetic images with original images to enhance datasets and verify the effectiveness of synthetic datasets. We use different numbers and sizes of images for training. Likewise, the Structural Similarity Index (SSIM) and Mean Square Error (MSE) were employed to assess picture quality. Our study quantifies the SSIM difference between the synthetic and actual images. When additional images are used for training, the synthetic image exhibits a high degree of resemblance to the genuine image. The highest SSIM value was achieved when using 200 total images as input and 32×32 image size. Further, we augment the original picture dataset with synthetic pictures and compare the original image model to the synthesis image model. For this experiment, we are using the latest iterations of Yolo, Yolo V3, and Yolo V4. After mixing the real image with the synthesized image produced by LSGAN, the recognition performance has been improved, achieving an accuracy of 84.9% on Yolo V3 and an accuracy of 89.33% on Yolo V4.

Penelitian ini adalah untuk mengetahui pengaruh penggunaan media pembelajaran dalam dunia pendidikan. Media pembelajaran adalah suatu alat yang digunakan pengajar untuk menyampaikan pesan kepada pembelajar agar pesan itu sampai kepada pembelajar dengan baik. Penggunaan media pembelajaran juga sangat berpengaruh kepada pembelajar, pembelajar lebih mudah untuk memahami tujuan dan maksud dari materi pembelajaran, serta pembelajar juga bisa dapat mengembangkan rasa ingin tahu, dan mendapatkan pengetahuan yang lebih nyata dengan kondisi saat pelajaran dilaksanakan. Penelitian ini menggunakan pendekatan kualitatif, yaitu mendeskripsikan dan menguraikan tentang pengaruh penggunaan media pembelajaran dalam dunia pendidikan. Teknik pengumpulan data yang digunakan dalam penelitian ini adalah studi kepustakaan (Library Research) dimana studi kepustakaan adalah kegiatan mengumpulkan bahan-bahan yang berkaitan dengan penelitian yang berasal dari buku, jurnal-jurnal ilmiah, literatur-literatur dan publikasi-publikasi lain yang layak dijadikan sumber untuk penelitian yang akan di teliti penulis, dengan cara mendeskripsikan dan menguraikan data tersebut adalah melalui beberapa pendapat para ahli. Variabel penelitian adalah segala sesuatu yang berbentuk apa saja yang ditetapkan oleh peneliti untuk dipelajari sehingga diperoleh informasi tentang hal tersebut kemudian ditarik kesimpulannya. Variabel yang digunakan dalam penelitian adalah Variabel Bebas (Independent Variable) dan Variabel Terikat (Dependent Variable). Maka dengan menggunakan pendekatan kualitatif penelitian ini diharapkan bisa memberikan fakta-fakta secara komprehensif tentang pengaruh penggunaan media pembelajaran dalam dunia pendidikan. Manfaat dari penulisan ini adalah untuk menambah wawasan bagi para pembaca mengenai pentingnya media pembelajaran dalam dunia pendidikan.

Penelitian ini bertujuan untuk melihat seberapa jauh perkembangan Teknologi Informasi dan Komunikasi (TIK) dalam dunia pendidikan khususnya sekolah dasar. Pemanfaatan TIK dalam pendidikan pada penelitian ini lebih dikerucutkan lagi pada proses pembelajarannya. Guru dapat memanfaatkan TIK untuk memeprsiapkan proses pembelajaran dan atau ketika proses pembelajaran berlangsung. Dengan TIK guru dapat menambah bahan ajar dan mencari referensi tentang metode pembelajaran yang tepat untuk siswanya. Dalam pembelajaran guru dapat menyampaikan materi dengan lebih mudah diterima oleh siswa dengan bantuan pemanfaatan TIK. Penerapan TIK juga tidak hanya semata-mata langsung diterapkan, tetapi juga harus melihat karakteristik siswanya. Maka proses pembelajaran akan berkualitas dan bermakna dengan pemanfaatan TIK yang sesuai dengan karakteristik siswa.

Penelitian ini bertujuan untuk menganalisis ulang penggunaan media pembelajaran dalam meningkatkan hasil belajar IPA SD. Metode yang digunakan dalam penelitian ini merupakan metode meta analisis. Penelitian ini diawali dengan mencari topik yang relevan guna memudahkan penulis dalam mengumpulkan data. Data tersebut diperoleh dengan cara menelusuri hurnal-jurnal online melalui google academia dengan kata kunci Media Pembelajaran, Meningkatkan Hasil Belajar, IPA,Sekolah Dasar. Dari penelusuran yang dilakukan diperoleh 12 artikel tetapi yang relevan untuk digumakam hanya 6 artikel. Data-data yang telah diperoleh diolah kembali menggunakan metode kuantitatif. Berdasarkan hasil analisis penggunaan media dalam pembelajaran terbukti dapat meningkatkan hasil belajar siswa paling rendah 43% dan yang paling tinggi 91%. Penggunaan media pembelajaran sangat berpengaruh terhadap hasil belajar siswa dalam muatan pembelajaran IPA. Selain itu siswa juga mempunyai pengalaman yang berbeda dalam proses pembelajaran menggunakan media. Hal ini juga dapat meningkatkan kemampuan siswa dalam memahami materi pelajaran dengan mudah melalui penggunaan media selama proses pembelajaran.

Fuzzy clustering algorithms generally treat data points with feature components under equal importance. However, there are various datasets with irrelevant features involved in clustering process that may cause bad performance for fuzzy clustering algorithms. That is, different feature components should take different importance. In this paper, we present a novel method for improving fuzzy clustering algorithms that can automatically compute individual feature weight, and simultaneously reduce these irrelevant feature components. In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the best known. We first consider the FCM objective function with feature-weighted entropy, and construct a learning schema for parameters, and then reduce these irrelevant feature components. We call it a feature-reduction FCM (FRFCM). During FRFCM processes, a new procedure for eliminating irrelevant feature(s) with small weight(s) is created for feature reduction. The computational complexity of FRFCM is also analyzed. Some numerical and real datasets are used to compare FRFCM with various feature-weighted FCM methods in the literature. Experimental results and comparisons actually demonstrate these good aspects of FRFCM with its effectiveness and usefulness in practice.

This study aims to determine differences in learning outcomes of Mathematics of primary school students usingproblem based learning model. The type of research used is the meta-analysis of research that has been donebefore. This research uses quantitative synthesis method. The purpose of this study is to determine the effect ofusing problem based learning model on elementary mathematics subjects. Data collection in this research isdone by searching journal through google scholar. Keywords used for journal search are: improving the resultsof elementary mathematics learning, problem based learning. From the model of problem based learningselected 10 research results to be analyzed further in% form. Based on the results of the analysis of 10 researchresults, it can be concluded that the learning with Problem based learning model (PBL) can improve thelearning outcomes of learners learner. Increased learning outcomes from the lowest 5% to the highest 40%, withan average of 22.9%.

Penelitian ini bertujuan untuk mengetahui pelaksanaan pembelajaran daring di SMA Negeri 1 Gabus, Kab. Grobogan pada masa pandemi covid-19. Metode penelitian yang digunakan adalah metode kualitatif deskriptif dengan analisis data interaktif yang meliputi 1) pengumpulan data, 2) reduksi data, 3) penyajian data, 4) penarikan kesimpulan. Teknik pengumpulan data pada penelitian ini menggunakan teknik 1) observasi, 2) wawancara, 3) dokumentasi dengan sumber data guru, siswa, orang tua, dan sumber pendukung waka kurikulum. Hasil penelitian menunjukkan bahwa proses pembelajaran di SMA N 1 Gabus, Kab. Grobogan selama masa pandemi covid-19 berlangsung secara daring dengan mengadakan pendampingan atau bimbingan guru. Guru melaksanakan proses pembelajaran dengan tahap perencanaan, pelaksanaan, dan evaluasi. Pelaksanaan pembelajaran daring menimbulkan problematika yang kemudian mendorong adanya upaya untuk mengatasi problematika yang dilakukan oleh guru, siswa, orang tua / wali murid, beserta waka kurikulum untuk mensukseskan pelaksanaan pembelajaran daring

The purpose of this study is to examine the effect of audit quality on earnings management. The audit quality is proxied by the Public Accounting Firm size (big-four and non-big four) and auditor’s industry specialisation. This study used four control variables, which are firm size, leverage, operating cash flow ratio and growth prospect. This study used secondary data derived from the financial statements of listed companies in Indonesia Stock Exchange in 2010-2011. Based on the method of purposive sampling method and was obtained 174 observations. The technique for examining the hypothesis is multiple regression analysis. The results show that accounting firm size does not significantly influence on the earnings management. Auditor’s industry specialisation has a negative effect on the earnings management. Of the four control variables used in this study, only the operating cash flow and growth that effect on earnings management, while the other two variables, namely the firm size and leverage, have no effect.

This study aims to explore students' attitudes toward teacher feedback. The study used a triangulation of participants and methods in which the practice of feedback was seen from the perspectives of students and teachers collected from the quantitative data (questionnaires) and qualitative data (open-ended items in questionnaires and interviews). A total of 100 students participated in filling in the questionnaires and 21 of them were interviewed using a semi-structured format. In addition, there were 20 teachers who completed the questionnaires and 10 of them were interviewed using the same semi-structured format. The findings show that generally teachers and students have a marked preference for teacher feedback. The high preference for teacher feedback was mainly the result of the respondents' positive attitudes towards teacher feedback. Interestingly, student preferences for teacher feedback also stemmed from their awareness that teachers control grades. The data collected from the questionnaires and interviews indicated that students preferred teacher feedback that was specific since this kind of feedback would facilitate students in the revision process. Students also show a high preference for feedback which focused on language. Compared to feedback on content, feedback on form was considered to be more helpful. Students often complained that teacher feedback on content tended to be general and sometimes, contradictory to student ideas. Moreover, the interview data illustrated that teacher feedback contributed greatly to students' emotional states particularly their motivation and attitudes towards writing.

This research was conducted to improve learning result and creativity of third grade students of SD NegeriSidorejoLor 01 Salatiga in the third semester in Theme 6 Subtema 2 and 3 by applying the Learning Based Learning (PjBL) model. This study is a classroom action research (PTK) consisting of two cycles. Each cycle consists of two meetings, each of which consists of action planning, action implementation, observation and reflection and 1 evaluation meeting. Data obtained in this study were obtained from observation, document study, test. Data analysis technique used is descriptive quantitative and qualitative. The results showed that the application of learning model of Project Based Learning (PjBL) can improve student learning outcomes and creativity of third grstudents at SD NegeriSidorejoLor 01 Salatiga. At the pre cycle cycle percentage of student learning 46% and then increased in the first cycle as much as 72% and increased again to 92% in cycle II. While the creativity of students in the pre cycle of 29% increased to 51% in the first cycle of meeting 2 and increased to 90% in the second cycle of meeting 2.

BACKGROUND: Chronic kidney disease (CKD) is common and ranks among the leading causes of mortality and morbidity. This analysis aimed to present global CKD estimates using the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 to inform evidence-based policies for CKD identification and treatment. METHODS: This analysis focused on adults aged 20 years and older over the period 1990 to 2023, from 204 countries and territories. Data sources used were published literature, vital registration systems, kidney failure treatment registries, and household surveys. Estimates of CKD burden, including deaths, incidence, prevalence, and disability-adjusted life-years (DALYs), were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool. A comparative risk assessment approach estimated the proportion of cardiovascular deaths attributable to impaired kidney function and estimated risk factors for CKD. FINDINGS: Globally, in 2023, 788 million (95% uncertainty interval 743-843) people aged 20 years and older were estimated to have CKD, up from 378 million (354-407) in 1990. The global age-standardised prevalence of CKD in adults was 14·2% (13·4-15·2), a relative rise of 3·5% (2·7-4·1) from 1990. The region with the highest age-standardised prevalence was north Africa and the Middle East (18·0%; 16·9-19·4). Most people had stage 1-3 CKD, with a combined prevalence of 13·9% (13·1-15·0). In 2023, CKD was the ninth leading cause of death globally, accounting for 1·48 million (1·30-1·65) deaths, and the 12th leading cause of DALYs, with an age-standardised DALY rate of 769·2 (691·8-857·4) per 100 000. Impaired kidney function as a risk factor accounted for 11·5% (8·4-14·5) of cardiovascular deaths. High fasting plasma glucose, body-mass index, and systolic blood pressure were all leading risk factors for CKD DALYs. INTERPRETATION: CKD is a major global health issue, with rising prevalence and increasing importance as a cause of death and as a risk factor for cardiovascular death. A better understating of aetiology, appropriate screening, and implementation programmes are needed to translate advances in CKD treatment into improved patient outcomes. FUNDING: Gates Foundation, Wellcome, US National Kidney Foundation, and US National Institute of Diabetes and Digestive and Kidney Diseases.

The purpose of this study is to investigate the effect of ownership structure on profitability in the manufacturing sector. Independent variables used for this study are consisted of foreign ownership, government ownership, managerial ownership, institusional ownership, family ownership. Profitability is measured by ROA (Return On Assets), while firm size and leverage are used as the control variables. This study is used 224 samples of manufacturing companies listed in Indonesian Stock Exchange for the period 2010-2011. The results show that foreign ownership and leverage have a positive and significant effect to profitability. Family ownership has a negative and significant effect to profitability. However, government ownership, managerial ownership, institutional ownership and firm size have no influence to profitability.

This article examines the effect of state ownership on the labor cost stickiness of firms in 22 European countries. States are more likely to interfere in the decision-making processes of state-owned enterprises (SOEs) and demand firm activities that are desirable from a socio-political perspective. For example, to win political support, politicians may instruct SOEs to avoid layoffs to minimize unemployment rates. The varied objectives of SOEs also make it more difficult to control managers' behavior, leaving more room for managerial discretion and the pursuit of self-interests through empire-building behavior. Both state intervention and managerial self-interest restrain managers from laying off employees or reducing employee wages when sales decrease, which may lead to greater labor cost stickiness. Data from 1993 to 2012 reveal that SOEs exhibit greater labor cost stickiness than private firms, and their labor cost stickiness also varies predictably with socio-political variables such as election years and left-wing governments.

Penelitian ini bertujuan untuk mencari alternatif upaya meningkatkan minat baca siswa khususnya dikalangan sekolah dasar. minat baca merupakan suatu pengaruh yang besar bagi siswa . Upaya meningkatkan minat baca siswa sekolah dasar menjadi tanggung jawab bersama, antara siswa itu sendiri, guru maupun orang tua. Namun rendahnya minat baca siswa di sekolah dasar menjadi salah satu halangan, kurangnya keinginan dan kemauan dari siswa itu sendiri, guru juga belum mengharuskan siswa untuk membaca buku saat pembelajarn yang diajarkan kepada siswa. Dalam upaya meningkatkan minat baca siswa sekolah dasar sebaiknya siswa diberi dukungan agar minat baca itu muncul dari diri siswa dan dikenalkan dengan bahan bacaan supaya siswa tersebut terbiasa membaca, maka dari itu kebiasaan membaca siswa dimasa duduk di bangku sekolah dasar akan menumbuhkan minat baca yang tinggi hingga siswa tumbuh dewasa. Penelitian ini dilakukan dengan merumuskan masalah penelitian mencari refrensi-refrensi dari jurnaljurnal yang relevan dan yang sejenis untuk dianalisis datanya, jurnal dikumpulkan dengan dengan menelusuri internet melalui Google Chendikia dan/atau Google Scholar. Data-data yang didapat dianalisis dan dibandingkan metode penelitian ini menggunakan Jenis penelitian deskriktif dengan pendekatan kuantitatif. Dari hasil analisis dapat meningkatkan minat baca siswa sekolah dasar.

Tourism development has often been regarded as an effective strategy for poverty reduction and sustainable livelihoods. However, tourism often triggers transformations of traditional livelihoods and complete dependence on tourism-based income. Presenting the case of Komodo village on Komodo Island, Indonesia, this study provides an empirical evidence for such transformation. Based on qualitative methods, this article discusses the ways in which tourism development has led the local fishing community to give up their fishing to become fully dependent on selling souvenirs. Although currently, the souvenir business offers adequate return for local people, potential threats to this new livelihood, like a limited market, fierce competition, a short tourist season, and high dependence on cruise ship visits, are looming large. If tourism declines, local people will be left with no options to sustain their livelihood.