scholarly journals Analysis of Efficiency for Zakat Management Organization in Indonesia: A Comparison Study of Super Efficiency and Free Disposal Hull

2021 ◽  
Vol 5 (2) ◽  
pp. 147-166
Author(s):  
Muhamad Nafik Hadi Ryandono ◽  
A Syifaul Qulub ◽  
Eko Fajar Cahyono ◽  
Tika Widiastuti ◽  
Elsi Mersilia Hanesti ◽  
...  
Keyword(s):  
Social Organization ◽  
Potential Importance ◽  
Comparison Study ◽  
Output Variable ◽  
Free Disposal Hull ◽  
Super Efficiency ◽  
Free Disposal ◽  
Total Potential ◽  
Input Variables ◽  
The Government

This research aims to analyze the efficiency level of fourteen Zakat Management Organizations (ZMO) in Indonesia. This study uses a quantitative approach with the method of Free Disposal Hull (FDH) and the Super Efficiency (SE) method. Socialization Expense, Operational Expense, and Salary Expense are the input variables, while zakah fund collection and zakah distribution become the output variables. Empirical findings show that ZMO Corp 4 has the highest efficiency level, which analyzed through both methods of FDH or SE. ZMO managed by the government is the most efficient ZMO compared to the others who managed by private group and social organization. Total Potential Importance (TPI) shows that the output variable that requires the most significant adjustment is the zakat distribution, which is 12.66%

scholarly journals Order Picking and E-Commerce: Introducing Non-Parametric Efficiency Measurement for Sustainable Retail Logistics

2021 ◽  
Vol 16 (4) ◽  
pp. 846-858
Author(s):  
Matthias Klumpp ◽  
Dominic Loske
Keyword(s):  
Goodness Of Fit ◽  
New Technologies ◽  
Order Picking ◽  
Free Disposal Hull ◽  
Free Disposal ◽  
Efficiency Assessment ◽  
Parametric Data ◽  
Proposed Model ◽  
Dea Models ◽  
Non Parametric

Order picking is a crucial but labor- and cost-intensive activity in the retail logistics and e-commerce domain. Comprehensive changes are implemented in this field due to new technologies like AI and automation. Nevertheless, human worker’s activities will be required for quite some time in the future. This fosters the necessity of evaluating manual picker-to-part operations. We apply the non-parametric Data Envelopment Analysis (DEA) to evaluate the efficiency of n = 23 order pickers processing 6109 batches with 865,410 stock keeping units (SKUs). We use distance per location, picks per location, as well as volume per SKU as inputs and picks per hour as output. As the convexity axiom of standard DEA models cannot be fully satisfied when using ratio measures with different denominators, we apply the Free Disposal Hull (FDH) approach that does not assume convexity. Validating the efficiency scores with the company’s efficiency assessment, operationalized by premium payments shows a 93% goodness=of-fit for the proposed model. The formulated non-parametric approach and its empirical application are promising ways forward in implementing empirical efficiency measurements for order picking operations within e-commerce operations.

scholarly journals A fuzzy system for cloacal temperature prediction of broiler chickens

2012 ◽  
Vol 42 (1) ◽  
pp. 166-171 ◽  
Author(s):  
Leandro Ferreira ◽  
Tadayuki Yanagi Junior ◽  
Wilian Soares Lacerda ◽  
Giovanni Francisco Rabelo
Keyword(s):  
Decision Support ◽  
Fuzzy System ◽  
Broiler Chickens ◽  
Broiler Chicken ◽  
Fuzzy Inference ◽  
Air Velocity ◽  
Output Variable ◽  
Average Standard Deviation ◽  
Inference System ◽  
Input Variables

Cloacal temperature (CT) of broiler chickens is an important parameter to classify its comfort status; therefore its prediction can be used as decision support to turn on acclimatization systems. The aim of this research was to develop and validate a system using the fuzzy set theory for CT prediction of broiler chickens. The fuzzy system was developed based on three input variables: air temperature (T), relative humidity (RH) and air velocity (V). The output variable was the CT. The fuzzy inference system was performed via Mamdani's method which consisted in 48 rules. The defuzzification was done using center of gravity method. The fuzzy system was developed using MAPLE® 8. Experimental results, used for validation, showed that the average standard deviation between simulated and measured values of CT was 0.13°C. The proposed fuzzy system was found to satisfactorily predict CT based on climatic variables. Thus, it could be used as a decision support system on broiler chicken growth.

scholarly journals Legalitas Peremponang atau Muhabet sebagai Organisasi Kemasyarakatan

SASI ◽  
2019 ◽  
Vol 25 (2) ◽  
pp. 173
Author(s):  
Reny Heronia Nendissa
Keyword(s):  
Social Organization ◽  
Community Organizations ◽  
Conceptual Approach ◽  
The Government ◽  
Research Type

This writing aims to determine Peremponang or Muhabet or with other names can be categorized as community organizations based on Law Number 7/2013 as amended by Perpu No. 2/2017 because there are still many Peremponang or Muhabet or with other names in Ambon City and Maluku Province which have not been registered as a social organization. This writing uses normative juridical research type with the statute approach and conceptual approach. The results of the study explained that Peremponang or Muhabet or by other names had in fact been there even hundreds of years ago but had not been legalized and registered as mass organizations based on statutory regulations. Suggestions from this writing are. the government must make an inventory of the existence of women or muhabet or with other names in Ambon City and Maluku Province in general and advise to register so that it is not considered illegal other than that the rights and obligations of Ormas can be carried out properly especially the government's responsibility to empower Ormas, so that community welfare can be realized through women or muhabet or with other names.

scholarly journals WHEN BIAS KILLS THE VARIANCE: CENTRAL LIMIT THEOREMS FOR DEA AND FDH EFFICIENCY SCORES

2014 ◽  
Vol 31 (2) ◽  
pp. 394-422 ◽  
Author(s):  
Alois Kneip ◽  
Léopold Simar ◽  
Paul W. Wilson
Keyword(s):  
Central Limit ◽  
Limit Theorems ◽  
Central Limit Theorems ◽  
Data Envelopment ◽  
Free Disposal Hull ◽  
Average Efficiency ◽  
Free Disposal ◽  
Monte Carlo Experiments ◽  
The Individual ◽  
Individual Scores

Data envelopment analysis (DEA) and free disposal hull (FDH) estimators are widely used to estimate efficiencies of production units. In applications, both efficiency scores for individual units as well as average efficiency scores are typically reported. While several bootstrap methods have been developed for making inference about the efficiencies of individual units, until now no methods have existed for making inference about mean efficiency levels. This paper shows that standard central limit theorems do not apply in the case of means of DEA or FDH efficiency scores due to the bias of the individual scores, which is of larger order than either the variance or covariances among individual scores. The main difficulty comes from the fact that such statistics depend on efficiency estimators evaluated at random points. Here, new central limit theorems are developed for means of DEA and FDH scores, and their efficacy for inference about mean efficiency levels is examined via Monte Carlo experiments.

scholarly journals Incremental Granular Model Improvement Using Particle Swarm Optimization

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 390 ◽  
Author(s):  
Chan-Uk Yeom ◽  
Keun-Chang Kwak
Keyword(s):  
Particle Swarm Optimization ◽  
Fuzzy Numbers ◽  
Particle Swarm ◽  
Housing Price ◽  
Pso Algorithm ◽  
Output Variable ◽  
Swarm Optimization ◽  
Number Of Clusters ◽  
Model Improvement ◽  
Input Variables

This paper proposes an incremental granular model (IGM) based on particle swarm optimization (PSO) algorithm. An IGM is a combination of linear regression (LR) and granular model (GM) where the global part calculates the error using LR. However, traditional CFCM clustering presents some problems because the number of clusters generated in each context is the same and a fixed value is used for fuzzification coefficient. In order to solve these problems, we optimize the number of clusters and their fuzzy numbers according to the characteristics of the data, and use natural imitative optimization PSO algorithm. We further evaluate the performance of the proposed method and the existing IGM by comparing the predicted performance using the Boston housing dataset. The Boston housing dataset contains housing price information in Boston, USA, and features 13 input variables and 1 output variable. As a result of the prediction, we can confirm that the proposed PSO-IGM shows better performance than the existing IGM.

scholarly journals Social Organization Participation, Government Governance and the Equalization of Basic Public Services: Evidence from China

2019 ◽  
Vol 16 (16) ◽  
pp. 2996 ◽  
Author(s):  
Gangqiang Yang ◽  
Yongyu Xue ◽  
Yuxi Ma
Keyword(s):  
Social Organization ◽  
Public Services ◽  
Generalized Method Of Moments ◽  
Mediation Effect ◽  
Public Science ◽  
Social Organizations ◽  
Linkage Effect ◽  
Government Governance ◽  
The Government ◽  
The Relationship

This paper uses the methods of System Generalized method of moments (SYS-GMM), mediation effect and linkage effect to investigate the relationship among social organization participation, government governance and the equalization of basic public services from 2007 to 2017 in China. The empirical results show that the participation of social organizations and improvement in the government governance can promote the equalization of basic public services. The government has a greater capacity to drive the equalization of basic public services, but the density of social organizations can serve as a mediator in the equalization of basic public services. The government governance and social organization density have a strong linkage effect, but the link with social organization quality is weak. Furthermore, a linkage effect is evident in medical and health care, public education, environmental protection, and public culture but not in public science and social welfare.

scholarly journals How Efficiently Do Elite US Universities Produce Highly Cited Papers?

Publications ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 4 ◽  
Author(s):  
Klaus Wohlrabe ◽  
Félix de Moya Anegon ◽  
Lutz Bornmann
Keyword(s):  
Research Evaluation ◽  
Research Output ◽  
Harvard University ◽  
Institutional Research ◽  
Free Disposal Hull ◽  
Highly Cited Papers ◽  
Boston College ◽  
Free Disposal ◽  
Data Efficiency ◽  
Highly Cited

While output and impact assessments were initially at the forefront of institutional research evaluations, efficiency measurements have become popular in recent years. Research efficiency is measured by indicators that relate research output to input. The additional consideration of research input in research evaluation is obvious, since the output depends on the input. The present study is based on a comprehensive dataset with input and output data for 50 US universities. As input, we used research expenses, and as output the number of highly-cited papers. We employed Data Efficiency Analysis (DEA), Free Disposal Hull (FDH) and two more robust models: the order-m and order-α approaches. The results of the DEA and FDH analysis show that Harvard University and Boston College can be called especially efficient compared to the other universities. While the strength of Harvard University lies in its high output of highly-cited papers, the strength of Boston College is its small input. In the order-α and order-m frameworks, Harvard University remains efficient, but Boston College becomes super-efficient. We produced university rankings based on adjusted efficiency scores (subsequent to regression analyses), in which single covariates (e.g., the disciplinary profile) are held constant.

SOLUTION METHODS FOR NONCONVEX FREE DISPOSAL HULL MODELS: A REVIEW AND SOME CRITICAL COMMENTS

2014 ◽  
Vol 31 (01) ◽  
pp. 1450010 ◽  
Author(s):  
KRISTIAAN KERSTENS ◽  
IGNACE VAN DE WOESTYNE
Keyword(s):  
Technical Efficiency ◽  
Computational Efficiency ◽  
Recent Article ◽  
Free Disposal Hull ◽  
Free Disposal ◽  
Solution Methods ◽  
Minimum Costs ◽  
Empirical Illustration

This note first succinctly summarizes the currently available methods to solve the various nonconvex free disposal hull (FDH) models for technical efficiency as well as for minimum costs. It also offers some empirical illustration as to their computational efficiency. Second, this note briefly points out that the recent article by (26) and its correction by (4) proposing an extended enumeration method to solve for technical efficiency evaluated relative to this family of FDH models contain no original results.

Adjusting the errors of the GM(1, 2) grey model in the financial data series using an adaptive fuzzy controller

2016 ◽  
Vol 6 (3) ◽  
pp. 341-352 ◽  
Author(s):  
Marcel Bolos ◽  
Ioana Bradea ◽  
Camelia Delcea
Keyword(s):  
Fuzzy Controller ◽  
Financial Data ◽  
Data Series ◽  
Output Variable ◽  
Content Type ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Grey Models ◽  
The Status ◽  
Input Variables

Purpose The purpose of this paper is to focus on the adjustment of the GM(1, 2) errors for financial data series that measures changes in the public sector financial indicators, taking into account that the errors in grey models remain a key problem in reconstructing the original data series. Design/methodology/approach Adjusting the errors in grey models must follow some rules that most often cannot be determined based on the chaotic trends they register in reconstructing data series. In order to ensure the adjustment of these errors, for improving the robustness of GM(1, 2), was constructed an adaptive fuzzy controller which is based on two input variables and one output variable. The input variables in the adaptive fuzzy controller are: the absolute error ε i 0 ( k ) [ % ] of GM(1, 2), and the distance between two values x i 0 ( k ) [ % ] , while the output variable is the error adjustment A ε i 0 ( k ) [ % ] determined with the help of the above-mentioned input variables. Findings The adaptive fuzzy controller has the advantage that sets the values for error adjustments by the intensity (size) of the errors, in this way being possible to determine the value adjustments for each element of the reconstructed financial data series. Originality/value To ensure a robust process of planning the financial resources, the available financial data are used for long periods of time, in order to notice the trend of the financial indicators that need to be planned. In this context, the financial data series could be reconstituted using grey models that are based on sequences of financial data that best describe the status of the analyzed indicators and the status of the relevant factors of influence. In this context, the present study proposes the construction of a fuzzy adaptive controller that with the help of the output variable will ensure the error’s adjustment in the reconstituted data series with GM(1, 2).

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