Rancang bangun sistem intelijen bisnis untuk agroindustri teri nasi kualitas eskpor berskala usaha menengah
ABSTRACT
D. AGUS GOENAWAN. Business Intelligent System Development for Small and
Mediwn Scale Agro Industry of Export Quality Baby Anchovy (Stolephorus spp.). Under
the direction ofERIYATNO as a chairman, TEDDY PAWITRA, E. GUMBIRA SA'ID,
JOHN HALUAN, and MARIMIN as members of advisory committee.
The objective of this study was to provide a model of Business Intelligence
System (BIS) for mediwn scale agro industry of export quality baby anchovy that able to
extract external information, anticipate business environment changes, and make
appropriate and effective business decisions. The development of Business Intelligence
System used system approach, combined with Business Intelligence Roadmap (Moss &
Atre 2003). This model, called SIBITEX, has ability to process internal and external data
as well as providing intelligence analysis to anticipate the competitor's actions. Specific
system techniques like fuzzy logic, Case Based Reasoning, and Artificial Neural
Network were used in this study.
The SIBITEX model consisted of the Business Transaction modul that managed
all buying and selling transactions, and six business intelligence functions. The
Forecasting model used to predict raw material requirement and finished goods sold for
the next period. In Financial Feasibility model, management can determine feasibility of a
project based on NPV, IRR, PBP, and BIC Ratio. The AHP technique used in Limited
Raw Material model gave the priority action for management when supplies of anchovy
was limited. The Business Case Solution model used CBR based on solved business
cases. Using ANN, the Competitor's Action Anticipatory model could predict any impact
of competitor's action. Using expert system method, the Business Competition Analysis
model could simulate business decision options to help managers to win the business
competition.
The Fourier analysis was the proper technique in predicting raw materials supply
and finished goods demand. Agro industry investment with time projection of eight years
and processing capacity for 1.680 ton per year is feasible. The Limited Raw Material
showed that 'maintain relationship with suppliers' is the preferable purchasing decision.
The knowledge base of the Business Case Solution model was used to build an expert
system that could solve business cases more effective. The Competitor Action
Anticipatory model for the baby anchovy agro industry has eight variables for input layer,
three variables for output layer, and will give reasonable prediction when the hidden layer
consists of 13 variables, normalization data between -1 and 0, or between 0 and 1, and
use the Sigmoid Bipolar as activation function for the hidden and output layer. This
model gave the determination coefficient of about 80% and MSE less than 1.5%.
Validation through face validity (expert's judgment) showed SIBITEX could give
effective decisions and advices for management to win the business competitions.
Key words:
business intelligence system, baby anchovy, fuzzy logic, case based
reasoning, analytical hierarchy process, artificial neural network, expert
system
D. AGUS GOENAWAN. Business Intelligent System Development for Small and
Mediwn Scale Agro Industry of Export Quality Baby Anchovy (Stolephorus spp.). Under
the direction ofERIYATNO as a chairman, TEDDY PAWITRA, E. GUMBIRA SA'ID,
JOHN HALUAN, and MARIMIN as members of advisory committee.
The objective of this study was to provide a model of Business Intelligence
System (BIS) for mediwn scale agro industry of export quality baby anchovy that able to
extract external information, anticipate business environment changes, and make
appropriate and effective business decisions. The development of Business Intelligence
System used system approach, combined with Business Intelligence Roadmap (Moss &
Atre 2003). This model, called SIBITEX, has ability to process internal and external data
as well as providing intelligence analysis to anticipate the competitor's actions. Specific
system techniques like fuzzy logic, Case Based Reasoning, and Artificial Neural
Network were used in this study.
The SIBITEX model consisted of the Business Transaction modul that managed
all buying and selling transactions, and six business intelligence functions. The
Forecasting model used to predict raw material requirement and finished goods sold for
the next period. In Financial Feasibility model, management can determine feasibility of a
project based on NPV, IRR, PBP, and BIC Ratio. The AHP technique used in Limited
Raw Material model gave the priority action for management when supplies of anchovy
was limited. The Business Case Solution model used CBR based on solved business
cases. Using ANN, the Competitor's Action Anticipatory model could predict any impact
of competitor's action. Using expert system method, the Business Competition Analysis
model could simulate business decision options to help managers to win the business
competition.
The Fourier analysis was the proper technique in predicting raw materials supply
and finished goods demand. Agro industry investment with time projection of eight years
and processing capacity for 1.680 ton per year is feasible. The Limited Raw Material
showed that 'maintain relationship with suppliers' is the preferable purchasing decision.
The knowledge base of the Business Case Solution model was used to build an expert
system that could solve business cases more effective. The Competitor Action
Anticipatory model for the baby anchovy agro industry has eight variables for input layer,
three variables for output layer, and will give reasonable prediction when the hidden layer
consists of 13 variables, normalization data between -1 and 0, or between 0 and 1, and
use the Sigmoid Bipolar as activation function for the hidden and output layer. This
model gave the determination coefficient of about 80% and MSE less than 1.5%.
Validation through face validity (expert's judgment) showed SIBITEX could give
effective decisions and advices for management to win the business competitions.
Key words:
business intelligence system, baby anchovy, fuzzy logic, case based
reasoning, analytical hierarchy process, artificial neural network, expert
system