ANALISIS IMPLEMENTASI KURIKULUM 2013 DI SMA NEGERI 3 REJANG LEBONG, BENGKULU

This study aimed at analyzing qualitatively the implementation of K13 curriculum which has long been applied in the state senior high school number 3 of Rejang Lebong. The data were garnered using observations and interviews for the sake of eliciting information to answer the proposed problem. The other technique considered important was documentation to see the curriculum-based depictions and loads in the existing documents. After the data were gathered, the selection of data was undertaken in order to be displayed in findings; the data were analyzed and discussed; and they were concluded as the ultimate answer to the formulated problem. The present study drew a conclusion that the implementation of k13 curriculum ran well although some obstacles were faced such as learning facilities. The entire school’s community seemed to be committed to carry out the mandate of this national educational system’s law such as training for teachers’ competence, doing the duties of making lesson plans in the form of RPP and syllabi, providing a monthly report concerning the implementation of learning by teachers, and carrying out evaluations alongside giving guidance for teachers’ performances.

New Diagnostic Methods for Influential Observations in Linear Regression With Some Biased Estimation Methods

This thesis is concerned with the expansion of diagnostic methods in parametric regression models with some biased estimators. Of which, the Liu estimator, modified ridge estimator, improved Liu estimator and ridge estimator have been developed as an alternative to the ordinary least squares estimator in the presence of multicollinearity in linear regression models. Firstly, we introduce a type of Pena’s statistic for each point in Liu regression. Using the forecast change property, we simplify the Pena’s statistic in a numerical sense. It is found that the simplified Pena’s statistic behaves quite well as far as detection of influential observations is concerned. We express Pena’s statistic in terms of the Liu leverages and residuals. For numerical evaluation, simulated studies are given and a real data set has been analyzed for illustration. Secondly, we formulated Pena’s statistic for each point while considering the modified ridge regression estimator. Using this statistic, we showed that when modified ridge regression was used to mitigate the effects of multicollinearity, the influence of some observations could be significantly changed. The normality of this statistic was also discussed and it was proved that it could detect a subset of high modified ridge leverage outliers. The Monte Carlo simulations were used for empirical results and an example of real data was presented for illustration. Next, we introduce a type of Pena’s statistic for each point in the improved Liu estimator. Using this statistic, we showed that when the improved Liu estimator was used to mitigate the effects of multicollinearity, the influence of some observations could be significantly changed. The Monte Carlo simulations were used for empirical results and an example of real data was presented for illustration. The ridge estimator having growing and wider applications in statistical data analysis as an alternative technique to the ordinary least squares estimator to combat multicollinearity in linear regression models. In regression diagnostics, a large number of influence diagnostic methods based on numerous statistical tools have been discussed. Finally, we focus on ridge version of Nurunnabi et al. (2011) method for identification of multiple influential observation in linear regression. The efficiency of the proposed method is presented through several well-known data sets, an artificial large data with high-dimension and heterogeneous sample and a Monte Carlo simulation study.