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All Journal International Conference on Law, Business and Governance (ICon-LBG) Journal of Mathematics, Computation and Statistics (JMATHCOS)
Dian Kurniasari
University of Lampung
Law, Crime, Criminology & Criminal Justice Mathematics

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Application of Factor Analysis to Public Sector Integrity in Indonesia . Warsono; Armen Yasir; Dian Kurniasari; . Widiarti; Ridwan Saifuddin
International Conference On Law, Business and Governance (ICon-LBG) Vol 1 (2013): 1st ICon-LBG
Publisher : UBL

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.003 KB)

Abstract

The main purpose of this study is to analyze interrelationships among variables used on the survey of public sector integrity by Indonesia’s Corruption Eradication Commission (Komisi Pemberantasan Korupsi, KPK). The nine variables include corruption experiences, corruption perceptions, working environments, administration systems, the behavior of individuals, corruption prevention efforts, integrity experiences, integrity potencies, and integrity total. Using factor analysis, the approach is to explain these variables in terms of their common underlying dimensions, well-known as factors. Technically, factor analysis involves condensing the information contained in a number of original variables into a smaller set of new composite factors with a minimum loss of information. The results show that based on eigen values the first factor alone accounts for 70.7% of the common variance. The second factor alone accounts for 13,4%. The common variance of the nine variables explained by two factors is 84.1%. Using the varimax rotation and based on values of factor loadings the first factor makes high contribution to the variance of corruption experiences, corruption perceptions, working environments, the behavior of individuals, integrity experiences, and integrity total variables. The second factor makes high contribution to the variance of corruption prevention efforts and integrity potencies variables. Similar results, also, are obtained by quartimax rotation and equamax rotation
Maximum Likelihood Estimation of the Shape Parameters of the Generalized Lambda Distribution: A Finite-Sample Simulation Study Atika Ayu Listianingsih; Dian Kurniasari; Rini Wong Dani
Journal of Mathematics, Computations and Statistics Vol. 9 No. 3 (2026): Volume 09 Issue 03 (September 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/ka0bt992

Abstract

The Generalized Lambda Distribution (GLD) is a flexible four parameter distribution that can describe a wide range of symmetric, skewed and heavy tailed data patterns. However, its parameters are difficult to estimate because the likelihood equations are nonlinear and usually do not have analytical solution. This paper considers the finite-sample performance of maximum likelihood estimators for the two shape parameters of the Ramberg–Schmeiser GLD. The location and scale parameters are fixed at  and , while  and are numerically determined using the Newton–Raphson algorithm. A Monte Carlo simulation of 2000 replications is performed for sample sizes . The performance of the estimator is measured in terms of mean estimate, bias, empirical variance, mean squared error, observed-fisher-information-based variance and the ratio of the latter to empirical variance. The results show that as the sample size rises, the estimates become closer to the genuine parameter values. The bias, empirical variance and mean squared error are much reduced which shows that accuracy and precision are improved. For n = 1,000, the biases of   and   are 0.0022 and 0.0067, respectively. The ratios of observed Fisher information to empirical variance are 0.9693 for  and 0.9907 for , indicating that the asymptotic and empirical variance estimates are in good agreement. The results indicate that, for the parameter configuration and initialization scheme considered, the finite-sample performance of MLE using Newton–Raphson improves as the sample size increases. This improvement is reflected in lower bias, empirical variance, and MSE, as well as closer agreement between OFI-based and empirical variance estimates at n=1,000.
Co-Authors . Warsono . Widiarti Armen Yasir Dian Kurniasari Ridwan Saifuddin Rini Wong Dani