6 research outputs found
HUBUNGAN MEDIA SOSIAL INSTAGRAM TERHADAP MINAT DAN MODEL EDITING BERKARYA FOTOGRAFI PENGURUS UKM “HIMAFO” ANGKATAN 33 UNIVERSITAS NEGERI MALANG
No full textABSTRAK ABSTRAK Antoni Ryan Dwi. 2017. Hubungan media sosial instagram terhadap minat dan model editing berkarya fotografi pengurus UKM HIMAFO angkatan 33 universitas negeri malang. Skripsi, Jurusan Seni dan Desain, Fakultas Sastra, Universitas Negeri Malang. Pembimbing: (I) Drs.Triyono Widodo, M. Sn. (II) Ike Ratnawati, M.Pd. Kata Kunci: Instagram, minat dan model berkarya, fotografi. Media sosial instagram sedang trend digunakan karena mempunyai fitur yang menarik dengan mengandalkan layanan pengunggahan video berdurasi pendek dan foto untuk membagikan momen ataupun membagikan suatu bentuk kreativitas. Instagram kini tidak hanya menjadi kecenderungan, akan tetapi juga mempengaruhi cara membidik karya fotografi yang berpengaruh pada minat masyarakat untuk menekuni bidang fotografi. Instagram adalah salah satu media untuk memamerkan hasil karya-karya fotografi, yang mana akan mendapat apresiasi dari masyarakat yang melihat melalui like dan comment, hal tersebut secara tidak langsung dapat menginspirasi dan mempengaruhi gaya berkarya fotografi para pecinta fotografi karena melihat berbagai hasil karya yang dibagikan di instagram. Penelitian ini dilaksanakan dengan tujuan untuk mengetahui hubungan media sosial instagram terhadap minat dan model berkarya fotografi anggota UKM HIMAFO angkatan 33. Penelitian ini menggunakan pendekatan kuantitatif dengan metode analisa deskriptif. Penentuan responden menggunakan teknik purposive sampling dan pengumpulan data melalui wawancara yang menggunakan kuisioner. Langkah-langkah analisis data yang dilakukan adalah uji validitas reliabilitas, uji korelasi, Rank spearman yang terdiri dari uji koefisin koreasi, koefisien determinai, dan uji hipotesis. Hasil dari penelitian ini yaitu, media sosial instagram memiliki pengaruh yang signifikan terhadap minat berkarya fotografi anggota UKM HIMAFO angkatan 33, pengaruh tersebut yaitu sebesar 46,5%, dan sebanyak 53,5 anggota menggunakan media sosial instagram untuk keperluan lain selain berkarya. Media sosial instagram juga memiliki pengaruh yang signifikan terhadap model berkarya fotografi anggota UKM HIMAFO angkatan 33, model berkarya fotografi yang terdiri dari indikator aplikasi editing foto pada smartphone, dan proses editing. Aplikasi editing foto yang paling sering digunakan adalah snapseed. Pengaruh media sosial instagam terhadap model berkarya fotografi adalah sebesar 50,1% dan 49,9% tidak menggunakan model berkarya (editing foto) untuk mengunggah karya fotografi ke instagram. Media sosial instagram berpengaruh secara signifikan terhadap minat dan model berkarya fotografi, atau dalam artian lain memiliki korelasi yang sangat kuat dan pengaruh media sosial instagram terhadap minat dan model berkarya fotografi anggota UKM HIMAFO angkatan 33 adalah sebesar 65,1%. 34,9% anggota UKM HIMAFO angkatan 33 menggunakan media sosial instagram diluar dari faktor minat dan model berkarya
IMPLEMENTASI TINDAK LANJUT OBSERVASI KELAS DENGAN TEKNIK COACHING
Get PDFThe aim of this research is to explain the implementation of coaching in follow-up classroom observations as part of the principal's management. This research was conducted using descriptive qualitative methods. Researchers explain coaching techniques in follow-up efforts to classroom observations as a form of academic supervision. Class observation as a form of academic supervision is part of the principal's management which is the principal's duties and responsibilities. This class observation process is one of a series of teacher performance assessments. The coaching technique is one of the techniques for carrying out follow-up class observations by the school principal. With this technique, classroom observations can increase classroom observation activities which of course have a good impact on learning in general and have an impact on educational progress
Problematika Undang-Undang Nomor 6 Tahun 2023 Tentang Cipta Kerja Klaster Ketenagakerjaan Dalam Memberikan Perlindungan Dan Kesejahteraan Pekerja
Get PDFDalam penelitian ini mengkaji mengenai Undang-Undang Cipta Kerja Klaster Ketenagakerjaan dimana tujuan pemerintah adalah untuk meningkatkan perlindungan dan kesejahteraan pekerja dengan menciptakan lapangan kerja yang dilakukan melalui perubahan Undang-Undang sektor yang belum mendukung terwujudnya sinkronisasi dalam menjamin percepatan cipta kerja. Tujuan dari penelitian ini adalah untuk menganalisis urgensi pengesahan Undang-Undang Cipta Kerja dan menganalisis alasan Undang-Undang Cipta Kerja yang mempunyai tujuan memberikan perlindungan dan kesejahteraan pekerja justru mendapat penolakan dari para pekerja dan serikat pekerja. Metode penelitian yang penulis gunakan adalah penelitian hukum normatif. Tujuan disahkannya UU Cipta Kerja yaitu untuk memicu pertumbuhan investasi perlu dan perbaikan kualitas angkatan kerja, termasuk menginklusi para pekerja informal yang selama ini belum terakomodasi dalam UU No 13/2003. Karena itu, aspek ketenagakerjaan yang semestinya diatur di dalam UUCK adalah aspek pengembangan kualitas angkatan kerja, bukan menyangkut hak-hak pekerja, dengan tujuan menjadikan kualitas tenaga kerja sebagai daya tarik investasi.
Kata kunci : Cipta Kerja; Perlindungan; Kesejahteraan; Pekerja
Abstract
This study examines the Employment Cluster Job Creation Law where the government's goal is to increase the protection and welfare of workers by creating jobs through changes in sector laws that have not supported the realisation of synchronisation in ensuring the acceleration of job creation. The purpose of this study is to analyse the urgency of passing the Job Creation Law and to analyse the reasons why the Job Creation Law, which aims to provide protection and welfare for workers, has been rejected by workers and trade unions. The research method that the author uses is normative legal research. The purpose of the Job Creation Law is to trigger necessary investment growth and improve the quality of the labour force, including including informal workers who have not been accommodated in Law No. 13/2003. Therefore, the aspect of labour that should be regulated in the UUCK is the aspect of developing the quality of the workforce, not concerning workers' rights, with the aim of making the quality of the workforce an investment attraction.
Keywords: Job Creation; Protection; Welfare; Workers
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Association of Country Income Level With the Characteristics and Outcomes of Critically Ill Patients Hospitalized With Acute Kidney Injury and COVID-19
No full textIntroduction
Acute kidney injury (AKI) has been identified as one of the most common and significant problems in hospitalized patients with COVID-19. However, studies examining the relationship between COVID-19 and AKI in low- and low-middle income countries (LLMIC) are lacking. Given that AKI is known to carry a higher mortality rate in these countries, it is important to understand differences in this population.
Methods
This prospective, observational study examines the AKI incidence and characteristics of 32,210 patients with COVID-19 from 49 countries across all income levels who were admitted to an intensive care unit during their hospital stay.
Results
Among patients with COVID-19 admitted to the intensive care unit (ICU), AKI incidence was highest in patients in LLMIC, followed by patients in upper-middle income countries (UMIC) and high-income countries (HIC) (53%, 38%, and 30%, respectively), whereas dialysis rates were lowest among patients with AKI from LLMIC and highest among those from HIC (27% vs. 45%). Patients with AKI in LLMIC had the largest proportion of community-acquired AKI (CA-AKI) and highest rate of in-hospital death (79% vs. 54% in HIC and 66% in UMIC). The association between AKI, being from LLMIC and in-hospital death persisted even after adjusting for disease severity.
Conclusions
AKI is a particularly devastating complication of COVID-19 among patients from poorer nations where the gaps in accessibility and quality of healthcare delivery have a major impact on patient outcomes
At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods
No full textBy September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients
ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19
Get PDFThe International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use
