Manajemen idarah Masjid Agung Al-Mabrur Ungaran Kabupaten Semarang

Penelitian berfokus pada dua rumusan masalah, 1) Bagaimana Manajemen Idarah Masjid Agung Al-Mabrur Ungaran Kabupaten Semarang? 2) Apa saja faktor pendukung dan penghambat Implementasi Manajemen Idara Masjid Agung Al-Mabrur Ungaran Kabupaten Semarang?. Jenis penelitian yang digunakan skripsi ini adalah jenis penelitian kualitatif deskriptif, adapun sumber data yang digunakan yaitu sumber data primer dan sumber data skunder. Teknik pengumpulan data yang digunakan oleh penulis yaitu: metode observasi, wawancara (interview) dan metode dokumentasi. Adapun metode analisis yang digunakan oleh penulis, adalah analisis deskriptif kualitatif yaitu digunakan sebagai prosedur pemecahan masalah yang akan diteliti, dengan menggambarkan keadaan objek yang diteliti sekarang. Penulisan skripsi ini bertujuan untuk mengetahui bagaimana Manajemen Idarah Masjid Agung Al-Mabrur Ungaran Kabupaten Semarang, untuk mengetahui bagaimana faktor pendukung dan penghambat implementasi manajemen Idarah masjid Agung Al-Mabrur Ungaran Kabupaten Semarang. Terkait implementasi manajemen penulis fokus pada fungsi-fungsi manajemen yaitu planning, organizing, actuating, dan controlling yang dilakukan oleh pengurus Masjid. Hasil penelitian ini menunjukan bahwa implementasi Manajemen Idarah Masjid Agung Al-Mabrur Ungaran Kabupaten Semarang ada beberapa tahap yang diterapkan oleh pengurus ta'mir masjid dalam melaksanakan program dengan menerapkan fungsi-fungsi Manajemen, yang pertama fungsi Perencanaan proses perencanaan ini dilakukan pengrus Masjid Agung Al-Mabrur Ungaran sebelum melaksanakan program yang dikelompokan menjadi dua tahapan yaitu perencanaan jangka pendek dan panjang. Fungsi kedua yaitu Pengorganisasian pada fungsi ini diterapkan untuk membagikan job deskription, tugas dan tanggung jawab kepada anggotanya. Fungsi ketiga yaitu Penggerakan yang diterapkan dengan melakukan bimbingan kepada anggota, pemberian motivasi, dan komunikasi yang baik. Fungsi keempat yaitu Fungsi Pengawasan yang diterapkan pengurus Masjid untuk mengawasi bawahanya saat melaksanakan tugas yang diberikan sehingga jika ada yang melakukan kesalahan bisa di nasihati lalu diarahkan. Adapun faktor pendukung yaitu para pengurus ta'mir memiliki tingkat pendidikan yang tinggi, motivasi yang diberikan ketua ta'mir kepada bawahanya agar menumbuhkan semangat untuk melaksanakan tugasnya. Faktor penghambat yaitu adanya pengurus ta'mir bekerja sebagai pegawai dan tidak dapat stay lama memantau Masjid tetapi tetap melaksanakan tugas yang diberikan kepadanya, kurangnya ta'mir yang stay untuk mengontrol Masjid dan melaksanakan tugas saat waktu shalat telah tiba

Beyond gene-disease validity: capturing structured data on inheritance, allelic requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

Background: As the availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including secondary findings. // Methods: We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. // Results: For 36/65 gene-disease pairs, loss of function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using the CardiacG2P dataset as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. // Conclusions: Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is a pre-requisite for scalable genomic testing

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Point Biserial Correlation (PBC) for 1 to 20 clusters.

PBC was very similar for 3, 4 and 5 partitions. Therefore, we chose to build 4 clusters of patients (vertical dashed line). (PNG)</p

Distributions of the procedure–specific risks of HCV infection in case of contaminated equipment.

Distributions of the procedure–specific risks of HCV infection in case of contaminated equipment.</p

Panel of ward characteristics for each ward in the surgery hospital.

(A) HCV prevalence in each ward with their associated 95% confidence intervals. (B) Average number of procedures per patient. Procedure types are represented from the high-risk ones to the low-risk ones (from left to right). (C) Boxplots of average ward-specific risk of HCV infection, coloured according to the number of patients visiting these wards. Mean values are represented by purple diamond dots. Three wards are not represented because no patients underwent invasive procedures within them.</p

Sensitivity analysis for the cut-off value of the risk considered in the logistic regression.

Sensitivity analysis for the cut-off value of the risk considered in the logistic regression.</p

Panel of ward characteristics for each ward in the internal medicine hospital.

(A) HCV prevalence in each ward with their associated 95% confidence intervals. (B) Average number of procedures per patient. Procedure types are represented from the high-risk ones to the low-risk ones (from left to right). (C) Boxplots of average ward-specific risk of HCV infection, coloured according to the number of patients visiting these wards. Mean values are represented by purple diamond dots.</p

Average effect of simulated intervention on the overall risk of HCV infection during hospitalization.

Labels under bars correspond to the proportion of concerned patients for a given intervention for the four sub-scenarios considered in the analysis (Comparison groups A, B, C and D). As proportions of patients for the ward-focused scenario were chosen based on the number of cumulative patients in these wards, they were not exactly equal to the proportions given for patient-based scenarios.</p