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"Stres pada perawat dapat disebabkan oleh berbagai faktor, diantaranya adalah beban kerja. Beban kerja perawat di rumah sakit meliputi beban kerja fisik dan mental. Penyebab beban kerja dalam penelitian ini berfokus pada penyebab eksternal, yaitu: aspke tugas / pekerjaan, organisasi, aspek lingkungan. Penelitian ini bertujuan untuk mengetahui hubungan antara variabel beban kerja dengan stres kerja pada perawat IGD di Rumah sakit Pemerintah dan Rumah sakit Non Pemerintah. Penelitian menggunakan rancangan cross sectional terhadap perawat IGD. Analisis data secara analitik menggunakan uji korelasi product moment pearson untuk menguji hubungan beban kerja terhadap stres kerja ditiap rumah sakit digunakan uji statistik one way Anova.

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Hasil penelitian menunjukkan bahwa baik Rumah sakit Pemerintah maupun non Pemerintah berpotensi untuk terjadinya stres kerja pada perawat yang ditimbulkan oleh adanya beban kerja. Rekomendasi penelitian ini adalah perlu adanya rotasi, kesejahteraan diperhatikan, pengembangan jenjang karier, gathering/refreshing untuk menghindari kejenuhan.

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ABSTRACT

Stress in nurses can be caused by a variety of factors, including the workload. Workload of nurses in hospitals include physical and mental workload. Cause workload in this study focused on external causes, namely: aspke tasks / jobs, organizations, environmental aspects. This study aims to determine the relationship between the variable workload with work stress in nurses in the hospital emergency department and the Government Non-Government Hospitals. Studies using cross-sectional design of the ER nurses. Analytic data analysis using Pearson product moment correlation test to examine the relationship to work stress workload in each hospital used one way ANOVA statistical test.

The results showed that both hospital and non-government government has the potential to work on the stress caused by the presence of nurse workload. Recommendation of this study is the need for rotation, note welfare, career development, gathering / refreshing to avoid saturation."

"The restriction of banker's credit distribution caused many debitor candidates find another way on financing to adequate their needs. An alternative that used to choose is offering bonds. One thing that can not be avoid on investing is default risk. So that investor have to be selective to choose their investing instrument?s before put their money on it. To measure a risk of a bond, investor can see from its rating. The bond ratings issued by an institution called credit rating company. Publised creding announcement from the credit rating company sometimes already responded by the market before, so it becomes too late to used. This research has a purpose to analyze the prediction of the bond ratings and how they are determined, so we can predict the next credit rating. Unlike previous study,this research include both of accounting factors and accounting factors as a bond rating predictors and test explanatory power of the following five variables : (1) Leverage ratio, (2) Current ratio, (3) Size, (4) Growth and (5) Maturity structure. This research is a quantitative research which apply the dichotomous logistics regression model on the data to test the influence of five variables above to predict the bond ratings. The data consist of the manufacture companies listed in Indonesia Stock Exchange and PT.Pefindo on 2004-2006. The research question is asked whether accounting factors and non accounting factor can predict bond ratings if used together. The result of this research shows that leverage ratio is the best variable that represent accounting factor which had classification power to predict bond ratings. That is because the leverage ratio shows the proportion of the liabilities to the assets, where bond is one of liabilities component. The maturity that represent non accounting factor can not predict bond ratings because the data of maturity are homogenous. Based on the result, this research conclude that acconting factors and non accounting factor can not perform well if used together. The next research should be add more variables as the predictor and apply another models to predict bond rating, like Multi Discriminant Analysis (MDA) or Probit Model."