Application of Business Intelligence for Production Data Analysis in Agricultural Businesses
Keywords:
Business Intelligence, Data Analysis, Production Data, Agricultural Business, ecision MakingAbstract
The development of agricultural business activities generates various types of information that can be used to evaluate production processes, ranging from land conditions, crop types, planting periods, and the use of production inputs to the total harvest yield. However, the available data is not always processed into information that can assist business operators in determining appropriate production management strategies. This study aims to implement a Business Intelligence (BI) approach to process and analyze agricultural production data in order to generate information that supports the decision-making process. The research stages include data collection, the Extract, Transform, Load (ETL) process, data processing, analysis, and the presentation of results through an interactive dashboard. Production data is analyzed based on several aspects, such as production periods, crop types, land area, and harvest yields, to obtain an overview of agricultural business development and productivity. The implementation of Business Intelligence can present production data in a more structured form through tables, charts, and performance indicators. This information can be used to monitor changes in production output, compare performance across different periods, and support the evaluation of production activities based on the available data. Therefore, the implementation of Business Intelligence provides a more systematic approach to utilizing production data as a basis for generating information to support agricultural business management.
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