A decision tree algorithm for predicting amount of batik tulis lasem production by decision support system to support financial feasibility

Decision Support System for financial feasibility of the Batik Tulis Lasem Industry can process input data based-on Assumptions Value, Investment Costs, and Operational Costs into output in the form of recapitulation of Fund Sources, Projection of Profit a nd Loss and Projections of Cash Flows and value determinants of business feasibility such as: Net Present Value (NPV), Internal Rate of Return (IRR), and PayBack Period (PP). By this application, the researchers did a simulation asumtion value of Batik Tulis Lasem amount production. It was used 9 categories of Batik Tulis Lasem products, such as: Batik 1 Color Cheap, Batik 1 Color Medium, Batik 1 Color Expensive, Batik 2 Colors Cheap, Batik 2 Colors Medium, Batik 2 Colors Expensive, Batik 3 Colors Cheap, Batik 3 Colors Medium, and Batik 3 Colors Expensive. Simulation results are used as data in this study. The purpose of this study is to classify financial feasibility based-on the number of products produced. The algorithm used is Decision Tree. The data used is 100 records. Rule generated from the Decision Tree algorithm has an accuracy value of 95%. From the resulting the Decision Tree, there are 3 important rules can be taken in determining the amount of production.