APIP dalam Pelaksanaan Maturitas SPIP Government Internal Supervisory Apparatus in Implementing the Maturity of the Government Internal Control System

One of the problems that still occur in Indonesia today is the weakness of the Government Internal Control System (SPIP). This is indicated by the many findings of BPK's examination of weaknesses in the government's internal control system. In this case, there is a role for government internal auditors that are highly expected to create an effective and sustainable control system. This study aims to determine the effect of the role of APIP in implementing the Maturity of the SPIP at the Inspectorate Kab. South Solok. This research is a quantitative. The population and sample in this research were all government internal supervisory apparatus at the Inspectorate Kab. South Solok. Data collection technique used is through a questionnaire. The analysis technique used in this research is descriptive statistical analysis. The instrument were tested using validity test, reliability test, and normality test. Data analysis technique used is multiple linear regression analysis. The results showed that the role of leadership, internal supervisors, consultants, and catalysts had a positive effect on the implementation of the maturity of SPIP. While the role of quality assurance has a negative effect on the implementation of the maturity of SPIP.

Developing and Comparing of Paired Comparisons Models under Bayesian Principle.

The paired comparisons (PCs) is applicable in the situation, when items/ treatments are ranked to obtain the response, treatments presented in pairs. This study is carried out to develop some new paired comparison models named as the Rayleigh PC model, the Maxwell PC model, and the Nakagami PC model. Moreover, an Amendment is suggested in the existing van-Baaren VI PC model to introduce two-tie parameters. The Rayleigh PC model is also modified by introducing the parameter of no preference. The models are analyzed under Bayesian method. The posterior distributions for parameters are derived under non-informative and informative priors. The hyperparameters are elicited through the technique of prior predictive distributions. The ranking for treatments are obtained by the posterior estimates. To obtain posterior summaries, the following loss functions are considered in this study: quadratic loss function, weighted loss function, squared error loss function. The graphical depiction of marginal posterior distributions is given. Furthermore, the preference and predictive probabilities are evaluated for a current and future single PC, respectively. The posterior probabilities of the hypotheses are computed for comparing two parameters. Model appropriateness is checked through the χ2 test. The Lindley-Shannon information is enumerated for the amount of information in the priors. The Akaike information criterion and the Bayesian information criterion are measured for the model selection. The analysis is performed on the two real life data sets of five cigarette brands: Goldleaf, Marlboro, Dunhill, Benson & Hedges and Davidoff and four drinking water brands: Aquafina, Nestle, Kinley and Springley. The posterior summaries are obtained by the Gibbs sampling. Mostly SAS package is used for finding results.