Extract, Transform, Load Module in SOLAP for Indonesia Agricultural Commodity

The Spatial Online Analytical Processing (SOLAP) for Indonesia Agricultural Commodity has successfully developed in the previous study. The SOLAP system is integrated to the data warehouse which manages historical data of agricultural commodities including horticultures, food crops, plantations, and livestock. Indicators of the agricultural commodities are productivity, production and harvested area that are represented based on the district and year when the data are released. In order to provide update information to users, this study aims to develop an Extract, Transform, Load (ETL) module for the SOLAP. The data used in this study are productivity, production, and harvested area of agricultural commodities that were collected from Agricultural Statistics Database developed by Ministry of Agriculture Indonesia. The ETL module was created by adopting the Business Process Modeling Notation (BPMN) for conceptual modeling and Architecture Graph for logical design. The open source ETL application Kettle was used in the ETL module implementation. Testing phase using the verification and validation approach shows that the ETL module has been successfully executed as many 105,676 rows of data and all jobs implemented work properly.