Penerapan Metode Eksperimen untuk Meningkatkan Konsep Dasar Sains pada Anak Didik Kelompok A Tk Pkk Suruhwadang Kecamatan Kademangan Kabupaten Blitar

Tujuan penelitian ini adalah untuk memperoleh tentang kemampuan kognitif anak dalamhal konsep dasar sains dengan menggunakan metode eksperimen pada anak didik kelompokA TK PKK Suruhwadang sebelum dan sesudah dilakukan tindakan. Melakukan tindakanberupa penerapan metode eksperimen untuk meningkatkan kemampuan kognitif dalamkonsep dasar sains pada anak didik kelompok A TK PKK Suruhwadang. Mengetahui adatidaknya perbedaan kemampuan konsep dasar sains dengan menggunakan metodeeksperimen pada anak didik kelompok A TK PKK Suruhwadang antara sebelum dan setelahdilakukan tindakan. Rumusan masalah pada penitilian ini adalah apakah metode eksperimendapat meningkatkan kemampuan pemahaman konsep dasar sains pada anak didik kelompokA TK PKK Suruhwadang Kecamatan Kademangan Kabupaten Blitar. Untuk menjawabrumusan masalah digunakan jenis penelitian tindakan kelas (PTK) dengan model Kemmisdan Taggart melalui empat tahapan yaitu tahap perencanaan , pelaksanaan, observasi danrefleksiyang dilalui dengan dua siklus. Teknik pengumpulan data menggunakan teknikobservasi dan dokumentasi. Adapun instrumen yang digunakan adalah lembar observasikegiatan anak dan lembar observasi pembelajaran oleh guru.Hasil penelitian menunjukanbahwa kemampuan kognitif anak kelompok A pada konsep dasar sain pada pra penelitianmenunjukkan prosentase 56.25%. Setelah pelaksanaan siklus I tentang bidang kemampuankognitif pada konsep dasar sains menunjukkan 59% mengalami peningkatan .Setelahpelaksanaan siklus ke II naik menjadi 83%. Hal ini menunjukkan pelaksanaan siklus ke IItelah mencapai kriteria ketuntasan dan membuktikan bahwa dengan metode eksperimendapat meningkatkan kemampuan kognitif dalam konsep dasar sains

Discordance between 'actual' and 'scheduled' check-in times at a heart failure clinic

<div><p>Introduction</p><p>A 2015 Institute Of Medicine statement “Transforming Health Care Scheduling and Access: Getting to Now”, has increased concerns regarding patient wait times. Although waiting times have been widely studied, little attention has been paid to the role of patient arrival times as a component of this phenomenon. To this end, we investigated patterns of patient arrival at scheduled ambulatory heart failure (HF) clinic appointments and studied its predictors. We hypothesized that patients are more likely to arrive later than scheduled, with progressively later arrivals later in the day.</p><p>Methods and results</p><p>Using a business intelligence database we identified 6,194 unique patients that visited the Cleveland Clinic Main Campus HF clinic between January, 2015 and January, 2017. This clinic served both as a tertiary referral center and a community HF clinic. Transplant and left ventricular assist device (LVAD) visits were excluded. Punctuality was defined as the difference between ‘actual’ and ‘scheduled’ check-in times, whereby negative values (i.e., early punctuality) were patients who checked-in early. Contrary to our hypothesis, we found that patients checked-in late only a minority of the time (38% of visits). Additionally, examining punctuality by appointment hour slot we found that patients scheduled after 8AM had progressively earlier check-in times as the day progressed (P < .001 for trend). In both a Random Forest-Regression framework and linear regression models the most important risk-adjusted predictors of early punctuality were: later in the day appointment hour slot, patient having previously been to the hospital, age in the early 70s, and white race.</p><p>Conclusions</p><p>Patients attending a mixed population ambulatory HF clinic check-in earlier than scheduled times, with progressive discrepant intervals throughout the day. This finding may have significant implications for provider utilization and resource planning in order to maximize clinic efficiency. The impact of elective early arrival on patient’s perceived wait times requires further study.</p></div

Partial dependence plots of adjusted-predicted punctuality as a function of the top 4 predictive variables identified by the minimal depth analysis.

<p>These plots were derived from the Random Forest-Regression (RF-R) machine learning framework, and can be interpreted as the effect on the response for a one unit change in the predictor, while averaging over the effects of all the other 20 variables (shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0187849#pone.0187849.t001" target="_blank">Table 1</a>) in the RF-R.</p

Distribution of punctuality (differences between ‘actual’ and ‘scheduled’ check-in times).

<p>Dotted line represents a visit for which a patient checked-in exactly on time (punctuality = 0).</p

Predictiveness of punctuality, on basis of average minimal depth ranking of variables.

<p>Appointment hour slot was the most predictive variable, followed by visit type, and so forth.</p

Marginal plot of predicted punctuality as a function of appointment hour slot, visit type (categories collapsed to not new versus new to hospital), age (in quartiles), and race (categories collapsed to non-white versus white race).

<p>These plots were derived from the Random Forest-Regression (RF-R) machine learning framework.</p

Punctuality according to appointment hour slot.

<p>Punctuality according to appointment hour slot.</p

Cohort characteristics.

<p>Cohort characteristics.</p

Expression of potential targets and validated miRNA in human cardiomyopathy.

<p>Expression of potential targets and validated miRNA in human cardiomyopathy.</p

A representative network of molecules which are predicted targets of miRNAs 1, 214, 342, and 378.

<p>NF kappa B is the central nodal molecule of this network, but importantly, NF kappa B is not a predicted target to any of the altered miRNAs. The NF kappa B could be involved in pathogenesis as the molecules in the network are modulated by miRNAs, and the network function would change as a consequence. The solid arrow between molecules depicts experimentally proven relationship. A dashed line depicts inferred interaction based on experimental evidence. Solid feed-back circular line with an arrow (Auto-regulation). Representation of the shapes: Vertical Diamond–Enzyme; Horizontal Diamond–Peptidase; Equilateral Triangle–Phosphatase; Inverted Equilateral Triangle–Kinase; Solid line square–Cytokine; Dashed line square–Growth Factor; Circle–Other; Trapezoid–Transporter; Double line circle–Complex (like Beta ark).</p