memory of extension officer which is native who understand conditions in the site. This study also got information about existence of the rice miller from
society, owner of the rice miller visited, and so on. Then, this list was used as a guide to found rice miller in the field. Based on
field survey, there were 44 rice millers in Gekbrong. This number was insufficient to determine the efficiency of rice milling industry. In order to get more accurate
results, this study was expanded to neighboring sub-district. Purposively, Warungkondang selected as the study site by the main reason that Gekbrong was
part of this sub-district before regional expansion occurred. Thus, it was suspected that both sub-districts have similar characteristics of rice miller.
Similar to Gekbrong, this study also did not have a clear sample framework. So, sampling was done same way as in Gekbrong. Due to some limitations such as
materials, time, and field conditions, this study only used 50 rice millers in Warungkondang.
4.2 Data Processing and Analyzing
For this study, primary unit of observation is the rice milling business. Expected outputs of each business are rice, broken rice, rice bran, and chaff. All
outputs used in form of weight by kilogram. While input variables are used in this study include grain, working hour, and fuel.
Primary and secondary data are processed and analyzed by using quantitative and qualitative methods. Qualitative analysis is used to describe
characteristic of rice milling industry in study site. Meanwhile quantitative analysis is used to determine relative efficiency of rice milling industry in this
site. Model used in this study is DEA model. This model is used to analyze the
relative efficiency of rice milling industry. Efficient score value of efficiency equal to one shows that the rice milling business has been relatively efficient and
inefficient score value of efficiency less than one indicates rice milling business on the other conditions.
Referring to Koopmans definition about technical efficiency, the study used two requirements that both requirements must achieved by rice milling industry to
determine efficiency of rice milling, namely: 1.
Rice milling industry must have efficiency score equal to one. 2.
Rice milling industry must achieve zero slack condition for all variables used.
DEA was created as a tool to evaluate the performance of an activity in a unit entity organization Charnes, Cooper, Rhodes, 1978. DEA calculates the
efficiency of a DMU in one group of observation. The working principle of the DEA model is to compare the data input and output of an organizations data
decision-making unit DMU with other input and output data on the same DMU. This comparison is performed to obtain an efficiency score.
Assumptions of DEA: 1.
Entities evaluated by using a set of the same input to produce likewise set of the same output.
2. The data is positive and the weight is limited on positive values.
3. Input and output are variable.
4. In the presentation of Hayes, 2005, there are strengths and weaknesses of
DEA. DEA model used as a device to measure the performance has several advantages over other models, including:
5. DEA model can measure many input and output variables.
6. It does not require an assumption of a functional relationship between the
variables measured input and output. 7.
DMU is directly compared with one another. 8.
Input and output variable can have different measurement units. Meanwhile, limitation of DEA model, including:
1. It has sample specific.
2. It is an extreme point technique so that measurement error can be fatal.
3. It just measures the relative efficiency of DMU, not absolute efficiency.
4. Hypothesis testing is statistically difficult to be done. Using linear
programming formulation separately for each DMU calculations is manually difficult, especially for large-scale problems.
