criterion in supporting the decision process. The aim of MCDM methods is to help decision makers learn about the problems they face, to learn about
organizational values and objectives, and through exploring these in the context of the problem to guide them in identifying a preferred course of action Al-Harbi,
1999 in Jayarsa, 2005. In other words, MCDM is useful in circumstances which necessitate the consideration of different course of action, which can not be
evaluated by the measurement of a simple, single dimension. The evaluation of forestry industry based on regulation number P.172004
is involves of many criterions and indicators. Criterions here are consisting both qualitative and quantitative. It can say that the evaluation of forestry industry is a
multiple criteria decision making process. Commonly used MCDM methods in decision making are ranking and
rating. These methods assign the weight for each criterions and use weighted aggregation for the analysis outcomes Prakash, 2003. The evaluation of forestry
industry has been arranged on regulation number P.172004. The evaluation is carried out by assessing parameters which are included in each criterion and
indicator. The parameters has been weighted and scored based upon a rigorous definition of priorities. Forestry industry performance then will be categorizing
based on the aggregate scored of preferred options.
2.4. Database
Database is a collection of non – redundant data which is shareable among different applications representing the needs of individual or group users Laurin,
1996. The organization of database can be described in terms of record, fields,
and keys. Record is a group of related fields that stores data about the subject, called the master record or activity, which is known as the transaction record
Power, 2000. In general, it has five characteristics United Nations, 1996, i.e. 1 flexibility of the design; 2 availability of a controlled and standardized
approach to data input and updating; validation check in maintaining the integrity and consistency of the data elements; 4 availability of a security level; and 5
capability to minimize redundancy of data. A Database Managements System DBMS is software that defines a
database, stores the data, supports a query language, produces reports, and creates data entry screens. A DBMS performs three basic functions; it enables storage of
data in the database, retrieval of data from the database, and control of the database.
2.4.1. Storage
DBMS vary the configuration of the stored data. Mainframe systems store many large files, each containing many records, each record containing many data
items, and the data items containing many characters. The systems for microcomputer offer more constrained capacities because of limited primary and
secondary spaces.
2.4.2. Retrieval
The feature of DBMS most visible to the user is data retrieval. Current DBMS offer great flexibility in terms of how the information is retrieved and
displayed. With a sophisticated DBMS, the user can specify certain processing of
data customize the output e.d., reports or graphs in terms of heading and spacing.
2.4.3. Control
Much of the control activity of the DBMS is invisible to users. The users ask for some information and receive it without knowing the process that the
DBMS has performed. There are some capabilities of DBMS in a DSS Turban, 1995 are :
9 Capturesextract data for inclusion in a DSS database;
9 Quickly updates adds, deletes, changes data records and files;
9 Interrelates data from different sources;
9 Quickly retrieves data from a database for queries and reports;
9 Provides comprehensive data security protection from unauthorized access,
recovery capabilities, etc; 9
Handles personal and unofficial data so that users can experiment with alternative solutions based on their own judgment;
9 Performs complex retrieval and data manipulation tasks based on queries;
9 Tracks usage of data.
2.4.4. Three – Step in Database Design
Database applications are modeled using a three – step design process. In the first step, all the available information related to the application is organized,
using a high – level conceptual data model. At the conceptual level, the focus is on data types of the application, their relationships and constraints. The Entity
Relationship ER model is one of the most prevalent of all conceptual design tools Shekhar and Chawla, 2003. Conceptual modeling deals with the question
on how to describe in a declarative and reusable way the domain information of an application, its relevant vocabulary, and how to constrain the use of data, by
understanding what can be drawn from it. Entity – Relationship Analysis uses three major abstractions to describe data, these are Hawryszkiewycz, 1994:
• Entities, object that have independent physical or conceptual existence. • Relationship, which are meaningful interactions between the entities,
and
• Attributes, which are the properties of the entities and relationship.
The second step, also called the logical modeling phase, is related to the actual implementation of the conceptual data model in a commercial DBMS. The
logical model is the translation of the software independent conceptual model into a record structure defined in a particular Data Description Language DDL.
Nowadays, non spatial data are usually stored in relational databases and therefore the logical modeling consists of the design of tables in correspondence with the
conceptual model. In logical model, data requirements in order to implement the method will be identified Shekhar and Chawla, 2003.
The third and final step, modeling of the physical design, deals with the nuts and the bolts of the actual computer implementation of the database
applications. Issues related to the storage, indexing, management is handled at this level. Physical design described the data physically where every entity is set
according to the database software that will be used in the system Shekhar and Chawla, 2003.
2.5. Information System
