Odoo Data Mining Module Using Market Basket Analysis

Abstract

Odoo is an enterprise resource planning information system providing modules to support the basic business function in companies. This research will look into the development of an additional module at Odoo. This module is a data mining module using Market Basket Analysis (MBA) using FP-Growth algorithm in managing OLTP of sales transaction to be useful information for users to improve the analysis of company business strategy. The FP-Growth algorithm used in the application was able to produce multidimensional association rules. The company will know more about their sales and customers' buying habits. Performing sales trend analysis will give a valuable insight into the inner-workings of the business. The testing of the module is using the data from X Supermarket. The final result of this module is generated from a data mining process in the form of association rule. The rule is presented in narrative and graphical form to be understood easier.

Fig. 1. Research method.

Fig. 2. ERD on X Supermarket sales system.

Fig. 3. System flowchart.

Fig. 4. Generate frequent itemsets flowchart.

Fig. 5. Generate FP-Tree flowchart.

Fig. 6. Header table.

Fig. 7. Update frequent header table.

Fig. 8. FP-Tree.

Fig. 9. The view conditional pattern menu interface.

Fig. 10. The interface of view generated view pattern menu.

Fig. 11. The interface of table view menu.

Fig. 12. Pie diagram for the confidence of the pattern set.

Table 1. The capability ranking algorithm