The study aims at investigating the quality of internal auditing and its impact on nature, timing, and procedures of external audit, based on international auditing standards, in particular ISA (610). The standard ISA (610) requires the external auditors to assess independence, the scope of internal audit unit, competence, and due professional care of internal auditors as indicators that reflect the quality of internal audit performance before deciding to rely on internal auditors.

The sample of this study consisted of external auditors in Iraqi Solidary Companies for Auditing. A questionnaire was distributed to them via e-mail

Mangrove landscaping in the Segara Anakan Lagoon (SAL) is an adaptation pattern of mangrove ecosystems to live and grow in unstable areas. This research aimed to develop a mangrove landscape to mitigate the impacts of ocean waves, currents, and inundation due to climate change. The study was conducted in SAL and Cilacap Coast (CC) using the environmental properties and climate change data. The data obtained were analyzed using mapping and trendline analyses. The results showed that mangrove landscaping in Segara Anakan had four zones with Nypa frutican, Rhizophora styllosa, Aegiceras corniculatum, Rhizophora apiculata, Avicennia marina, Sonneratia alba identified as the best adaptation of mangrove species. Climate change give a high impa

      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin

In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.

The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana

Generalized Additive Model has been considered as a multivariate smoother that appeared recently in Nonparametric Regression Analysis. Thus, this research is devoted to study the mixed situation, i.e. for the phenomena that changes its behaviour from linear (with known functional form) represented in parametric part, to nonlinear (with unknown functional form: here, smoothing spline) represented in nonparametric part of the model. Furthermore, we propose robust semiparametric GAM estimator, which compared with two other existed techniques.